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January 6, 2015
Yet Another Handoff: The Intraoperative Handoff
In our many columns on handoffs in healthcare and other industries (see the full list at the end of today’s column) we thought we had covered almost every type of handoff. But though we’ve often discussed perioperative handoffs, there was one we have never discussed: the intraoperative handoff.
Perhaps it is apropos following last week’s Patient Safety Tip of the Week “Data Accumulates on Impact of Long Surgical Duration” that we discuss intraoperative handoffs. However, intraoperative changes in personnel occur not only during long surgical procedures. Hospitals that have extensive OR schedules commonly have nurses and anesthesia providers that work in shifts and those shift changes may take place during even normal duration surgical cases. In addition, work hour restrictions on physicians in training further increase the likelihood of transitions in anesthesia care. In fact, a large study at the Cleveland Clinic found that only 61% of cases had no anesthesia handoffs (Saager 2014). 21% of cases had one anesthesia handoff, 11% had two, 5% had three, and 3% had four or more handoffs.
We know that communication failures lead to errors and increased numbers of handoffs may be associated with adverse patient outcomes in multiple settings. The OR is no different. In the study by Saager and colleagues (Saager 2014) there was an 8% increase in the composite of mortality and morbidity for each increase of one handoff. For example, those with 2 transitions had a 17% increase in the composite. Moreover, the increased occurrence of complications with handoffs affected all the individual categories of the composite (cardiac, gastrointestinal, bleeding, infection). Their findings held up after adjustment for multiple potential confounding factors and in sensitivity analyses. The adverse effect of the handoffs was similar for attending anesthesiologists, directed residents, and CRNA’s. While the association does not prove causation, the association is nevertheless striking and implies the intraoperative handoffs were contributory factors to adverse outcomes. The Cleveland Clinic at the time of the study did not have a formal structured handoff process for intraoperative handoffs. The authors suggest adoption of formal protocols, including checklists, as a potential way to reduce the adverse impact of intraoperative handoffs on patient outcomes.
A recent study from the Massachusetts General Hospital assessed the impact of an electronic checklist on intraoperative handoffs between anesthesia providers (Agarwala 2015). The authors developed a checklist of information to be transferred at end-of-shift handoffs. Many of the items in the checklist were pre-populated from their anesthesia information management system (AIMS) and could be accessed easily by pressing a popup button on the AIMS screen. Use of the checklist was voluntary. The authors went to the OR and observed the intraoperative handoffs and assessed transfer of information using a structured assessment tool. They compared those handoffs that used the checklist against those that did not. They found significant increases in discussions about several medications (prophylactic antibiotics, vasopressors, and antiemetics) and increased information about intravascular lines and fluid balance. (Several other items also showed upward trends, though they did not reach statistical significance, perhaps because of small sample size.) Moreover, they also assessed whether the receiving anesthesia staff was able to recall accurately critical patient information passed on during the handoff. There was a significant improvement in the anesthesiologist knowing the antibiotic given and timing of the next dose. Similarly, those using the checklist were more able to recall the neuromuscular blocking agent used and the amount of fluids administered. In addition, introduction of the incoming anesthesiologist to the rest of the OR team increased from just 3% to over 50%. And discussion about potential areas of concern and post-op plan increased from less than 50% to over 90%. Providers of multiple types (anesthesiologists, CRNA’s, residents and fellows, faculty) were generally satisfied with use of the electronic checklist and use of the checklist, which was voluntary, increased to 74% by 8 months after its introduction.
Notably, using the electronic checklist did not increase the time needed for the intraoperative handoff. In fact, multiple providers responding to a post-implementation survey noted that the handoff felt less rushed when using the checklist.
Though the study did not measure impact of the improvements on patient outcomes, one would anticipate that the improvements could likely reduce untoward patient outcomes. Some of the potential errors that might arise from inadequate intraoperative handoffs include failure to give second doses of prophylactic antibiotics when needed, failure to reposition patients leading to compressive neuropathies, medication errors, failure to fully reverse neuromuscular blocking agents leading to post-op respiratory complications, and others. And intraoperative change in OR staff, particularly nursing, has been a risk factor in retained surgical items.
The Agarwala and Saager studies only addressed permanent (end-of-shift) handoffs. They did not address temporary handoffs like those that occur when anesthesiology staff go on breaks (typically 15-30 minutes). It’s important we don’t ignore the latter. Saager et al cite several studies from the 1970’s and 1980’s that concluded that breaks for anesthesia providers do not influence patient outcomes. But, anecdotally, we’ve seen multiple cases where such intraoperative handoffs were likely factors in adverse patient events. When an OR team member is gone for a short period of time and then returns, there is a natural tendency to think not much likely changed while he/she was gone and such assumptions may be disastrous.
Tan and Helsten previously described development of an AIMS-based electronic checklist for anesthesia handoffs at Barnes-Jewish Hospital and Washington University in St. Louis (Tan 2013). Their tool included several useful features and visual prompts to facilitate the handoff. First, the tabs containing the various checklist items took up only a portion of the computer screen, allowing critical patient information to still be visible. Like the electronic checklist developed by Agarwala and colleagues, they pre-populated checklist items where possible. But some items are difficult to abstract from the electronic record and need to be discussed. For example, “stage of surgery” is displayed in red with the word “DISCUSS” to prompt the two anesthesia providers to discuss the stage of surgery. There are also tabs for items like trends in vital signs, oxygenation, acute events (anesthetic or surgical), and the analgesia plan that should prompt specific discussion. And lastly, another tab for details of fluid management and lines.
Some unique issues arise at academic centers where attendings are supervising residents and fellows or sites where attendings may be supervising CRNA’s. At Cincinnati Children’s Medical Center a quality improvement project improved the intraoperative anesthesia handoff (Boat 2013). The quality improvement team consisted of pediatric anesthesiologists and CRNA’s with input from the IT department. They discussed key elements of a good handoff and the various components and analyzed aspects of their current handoff process. One barrier they identified was that the attending anesthesiologists often were not present in the OR when they did their handoff. Such handoffs were often done in the hallway, anesthesia lounge, main desk, or even on the phone. That left the in-room anesthesia provider (CRNA or resident/fellow) temporarily unsupervised. More important, it often left the in-room anesthesia provider out of the loop (i.e. they did not know what was discussed at the handoff). They developed a standardized checklist and a campaign to use the checklist and ensure the handoff was done in the OR, both done over multiple PDSA cycles. In addition, anesthesiologists who failed to comply with the new process received an email notifying them of the failure and a follow up phone call to ascertain the reason for the failure and reinforce the importance of the process. Compared to only 20% compliance with all elements of the handoff and performance of the handoff within the OR before the project, compliance increased to 100%. Their IT team later incorporated the handoff checklist into the intraoperative electronic medical record. That both allowed for documentation of the handoff and further encouraged compliance with the handoff protocol. In addition to standardization of the process with a checklist, key drivers were use of the “team huddle” approach with in-room anesthesia providers and the supervising attendings and ensuring situational awareness of the intraoperative environment at the time of the handoff. Having as “early adopters” those attendings who had previously experienced the impact of poor handoffs helped overcome the barrier of other attendings not recognizing the need for change.
Simulation has also been used to improve intraoperative handoffs. In a pilot study (Pukenas 2014) 10 anesthesiology residents participated in a one-day simulation-based handoff course. Each resident repeated simulated handoffs to deliberately practice with an intraoperative handoff checklist. One year later, 7 of the 10 residents participated in simulated intraoperative handoffs. Initially, the overall communication failure rate, defined as the percentage of handoff omissions plus errors, was 29.7%. After deliberate practice with the intraoperative handoff checklist, the communication failure rate decreased to 16.8%, and decreased further to 13.2% one year after the course.
Screenshots of the electronic checklists are provided in the full text of the Tan, Agarwala, and Boat papers. Another important point in the Agarwala study that we’ve made in our numerous columns on checklists: keep your checklists short! When they developed their electronic checklist they purposely kept the number of items to a minimum.
Today’s column has focused on the intraoperative handoff as it pertains to anesthesia staff. Intraoperative handoffs pertaining to nursing in the OR are beyond the scope of today’s column. But we refer you to the great resources AORN has on perioperative handoffs (AORN 2012).
Read about many other handoff issues (in both healthcare and other industries) in some of our previous columns:
May 15, 2007 “Communication, Hearback and Other Lessons from Aviation”
May 22, 2007 “More on TeamSTEPPS™”
August 28, 2007 “Lessons Learned from Transportation Accidents”
December 11, 2007 “Communication…Communication…Communication”
February 26, 2008 “Nightmares….The Hospital at Night”
September 30, 2008 “Hot Topic: Handoffs”
November 18, 2008 “Ticket to Ride: Checklist, Form, or Decision Scorecard?”
December 2008 “Another Good Paper on Handoffs”.
June 30, 2009 “iSoBAR: Australian Clinical Handoffs/Handovers”
April 25, 2009 “Interruptions, Distractions, Inattention…Oops!”
April 13, 2010 “Update on Handoffs”
July 12, 2011 “Psst! Pass it on…How a kid’s game can mold good handoffs”
July 19, 2011 “Communication Across Professions”
November 2011 “Restricted Housestaff Work Hours and Patient Handoffs”
December 2011 “AORN Perioperative Handoff Toolkit”
February 14, 2012 “Handoffs – More Than Battle of the Mnemonics”
March 2012 “More on Perioperative Handoffs”
June 2012 “I-PASS Results and Resources Now Available”
August 2012 “New Joint Commission Tools for Improving Handoffs”
August 2012 “Review of Postoperative Handoffs”
January 29, 2013 “A Flurry of Activity on Handoffs”
December 10, 2013 “Better Handoffs, Better Results”
February 11, 2014 “Another Perioperative Handoff Tool: SWITCH”
March 2014 “The “Reverse” Perioperative Handoff: ICU to OR”
September 9, 2014 “The Handback”
December 2014 “I-PASS Passes the Test”
Saager L, Hesler BD, You J, et al. Intraoperative transitions of anesthesia care and postoperative adverse outcomes. Anesthesiology. 2014; 121(4): 695-706.
Agarwala AV, Firth PG, Albrecht MA, et al. An Electronic Checklist Improves Transfer and Retention of Critical Information at Intraoperative Handoff of Care. Anesth Analg 2015; 120(1): 96-104
Tan JA, Helsten D. Intraoperative Handoffs. International Anesthesiology Clinics 2013; 51(1): 31-42 Winter 2013
Boat AC, Spaeth JP. Handoff checklists improve the reliability of patient handoffs in the operating room and postanesthesia care unit. Pediatric Anesthesia 2013; 23(7): 647-654
Pukenas EW, Dodson G, Deal ER, et al. Simulation-based education with deliberate practice may improve intraoperative handoff skills: a pilot study. J Clin Anesth 2014; 26(7): 530-538
AORN (Association of periOperative Registered Nurses). Patient Hand Off Tool Kit. 2012
January 13, 2015
More on Numeracy
Low health literacy is an issue well known to impact health outcomes. For years when we talked about health literacy we focused on reading levels and reading comprehension. But in our What’s New in the Patient Safety World columns for June 2012 “Parents' Math Ability Matters” and November 2014 “Out-of-Hospital Pediatric Medication Errors” we noted a study (AAP 2012) that showed that parents’ mathematics skills, independent of reading skills, may play a big role in some pediatric medication errors. The study (Marrese 2012) showed parents with math skills at the third grade level or below were five times more likely to measure the wrong dose of medication for their child than those with skills at the sixth grade level or higher. While about a third of the parents had low reading skills, 83% had poor “numeracy” skills, with 27% having skills at or below the third grade level. Parents with low numeracy may especially prone to make errors in tasks requiring dose measurement or measurement conversions.
The study highlighted the need to address numeracy skills of parents when communicating medication instructions. They also provided as an example having providers review and give parents pictures of dosing instruments filled to the correct amount for that prescription.
We suspected the same issues likely apply to adult medication errors as well. Now a new study in adults has demonstrated similar findings. Wong and colleagues assessed health literacy and numeracy in patients attending rural and urban rheumatologic practices in Australia (Wong 2014). The study utilized two validated and widely accepted tools for evaluation of health literacy plus a new practical tool that has not yet been validated. Word recognition was assessed using the Rapid Estimate of Adult Literacy in Medicine (REALM). Comprehension was assessed using the Test of Functional Health Literacy in Adults (TOFHLA). Practical comprehension and numeracy were then assessed by asking patients to follow prescribing instructions for 5 common rheumatology medications (they refer to this new tool as the “Rheumatology Literacy Guide”).
The investigators, somewhat to their surprise, found no statistically significant difference between the rural and urban populations. REALM scores indicated 15% of patients overall had a reading level ≤Grade 8 whereas 8% had marginal or inadequate functional health literacy as assessed by the TOFHLA.
However, most strikingly, they found significant proportions of the patient populations that incorrectly followed prescribing instructions for 2 drug regimens commonly prescribed for rheumatology patients. Dosing instructions for ibuprofen and methotrexate were incorrectly understood by 32% and 21% of patients, respectively.
That, of course, is of considerable concern particularly since methotrexate errors can result in serious adverse patient outcomes (see our What’s New in the Patient Safety World columns for July 2010 “Methotrexate Overdose Due to Prescribing Error” and July 2011 “More Problems With Methotrexate”).
The methotrexate question was “MTX and folic acid are used to treat rheumatoid arthritis. MTX comes in 10 mg tablets and folic acid in 0.5 mg tablets. A usual dose of MTX is 10 mg once a week and folic acid 0.5 mg once a day. Please count out how many of each tablet you would need for 1 week.”
The ibuprofen question was “Ibuprofen is a common anti-inflammatory medication. It is called a non-steroidal anti-inflammatory or NSAID. A common adverse effect is indigestion. It therefore needs to be taken just after a meal. Ibuprofen comes in 200 mg tablets. A common dose is 400 mg twice per day. How many tablets of ibuprofen per day is that?”
The patients handled instructions for the other three regimens (tramadol, prednisone, and alendronate) much better.
The two standardized validated tools were not very good at predicting who would err on the methotrexate or ibuprofen tasks.
The authors recommend the following strategies to address poor health literacy:
They also refer us to the Health Literacy Universal Precautions Toolkit developed for AHRQ by the North Carolina Network Consortium and others.
Wong et al. also stress that patients are often embarrassed about their ability to understand instructions and often overestimate their reading ability. In fact, some potential study subjects may have declined participation because of such embarrassment. So problems with health literacy and numeracy may, in fact, be underestimates.
They found risk factors for low health literacy that are similar to those found in the literature: male gender, non-English primary language, lack of university education, and lack of employment. Interestingly, they also found an association between low health literacy and low use of the Internet.
But don’t let education level fool you. In our May 7, 2013 Patient Safety Tip of the Week “Drug Errors in the Home” we described the considerable difficulty even well-educated patients had following some prescription regimens.
Therefore, use of the “teach back” technique is very important in ensuring that all patients or their caregivers really understand the instructions and correct dosing of medications. “Teach back” does require an investment of time. Practices often find that use of specially trained physician extenders may be useful in this regard. Hospitals often use pharmacists in this role. Anecdotally, we have found that patients are more willing to admit their difficulties following instructions to someone other than the physician, whether that person is a nurse, PA, NP, or pharmacist. In fact, we actually most often find out about such difficulties from our receptionists and other front office staff who deal with our patients frequently.
American Academy of Pediatrics (AAP). Parents’ Poor Math Skills May Lead to Medication Errors. AAP press release April 28, 2012
Marrese C, Dreyer B, Mendelsohn A, Moreira H, Yin HS. Parent Medication Dosing Errors: Role of Health Literacy and Numeracy (abstract). Pediatric Academic Societies (PAS) annual meeting April 28, 2012
Wong PKK, Christie L, Johnston J, et al. Observational Study: How Well Do Patients Understand Written Instructions?: Health Literacy Assessment in Rural and Urban Rheumatology Outpatients. Medicine 2014; 93(25): e129
AHRQ. Health Literacy Universal Precautions Toolkit. April 2010
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January 20, 2015
He Didn't Wash His Hands After What!
An observational study (Burcharth 2014 as reported by Bernard 2015) found that an astonishing 20% of attendees at an American surgical conference failed to wash their hands after visiting the restroom!
Admittedly, that may not be the same as hand hygiene in surgeons prior to surgery or prior to and after examining patients elsewhere. But we’ll bet that some of the same factors that influence hand hygiene apply in both situations. Four timely studies on the factors that influence the hand hygiene compliance of physicians and others lend some insight.
In the first, Squires and colleagues (Squires 2014) did semi-structured interviews with medical and surgical physicians and residents at a Canadian tertiary care center with two campuses, chosen via a quasi-experimental sampling strategy. They found 53 specific beliefs from 9 theoretical domains that influenced hand hygiene practices of participants. Sounds too ethereal for us! But the many statements from physicians they quote provide great insight.
They did find some key barriers and enablers found in previous studies: environmental context, social pressure, perception of the risk of cross-contamination, and a positive attitude about hand hygiene itself. But they also identified knowledge gaps about hand hygiene guidelines and evidence linking poor hand hygiene to healthcare-associated infections. Moreover, they identified a skill gap in the performance of hand hygiene.
Unlike studies in nurses, which show nurses tend to perform hand hygiene as a routine and automatic process, their study found that physicians required a conscious decision to perform hand hygiene and that cues, visual or otherwise, were often needed to encourage hand hygiene.
Social influences can come from colleagues and patients, though evidence for the influence of patients was weaker. They stress the importance of role models and “positive deviance” in encouraging hand hygiene. At least one of the respondents described a phenomenon we’ve often spoken about: if you see the leader of a team of rounding physicians and students stop to wash his/her hands, the rest of the team members are very likely to do the same.
(We’re not surprised about the relative lack of influence by patients. Patients still seldom speak up despite our efforts to get them to do so. They may be reluctant to potentially offend their physician. We’ve recommended trying a little humor to help patients feel more comfortable “challenging” their physician: use “Wanted…Armed and Dangerous!” posters in patient rooms, putting a picture of their attending physician on an old-west style wanted poster with a subcaption “If you see this individual, beware and make sure he/she washes his/her hands!”. But before you try that one, make sure your attending physicians also have a sense of humor!)
System constraints, as expected, were significant influences. Having easy access to hand hygiene resources at the point of patient contact was an almost universally mentioned factor. But they also found that high workloads were a barrier to hand hygiene.
They did find some differences across specialties. Fewer surgery than medicine physicians reported that other physicians influenced their hand hygiene practice. They speculate that, while this might reflect a sample size artifact, it could reflect that surgeons tend to work more independently than medicine physicians, who tend to work more in teams.
The Squires study lays the groundwork for further research and development of strategies to improve hand hygiene rates among physicians. It also has an extensive bibliography that you may find useful.
The second study (Chassin 2015) reports lessons learned from the Joint Commission Center for Transforming Healthcare hand hygiene quality improvement project. The eight hospitals in that project used Lean, Six Sigma and change management methods and saw a 70.5% increase in compliance (from 47.5% to 81.0%). This study included multiple types of healthcare workers, not just physicians.
They initially identified 41 different causes of hand hygiene noncompliance and condensed these into 24 groups of causes. But key causes varied greatly among the hospitals so each hospital focused on those issues most important at their facilities and organizations.
There is much overlap with barriers identified by Squires and colleagues and other previous researchers. Systems issues are common (hand hygiene facilities not readily available, empty hand dispensers, no soap at the sink, broken dispensers, etc.). But other system issues may include lack of space to free up hands for washing, need to go in and out of rooms frequently for supplies, etc. There are also occasional healthcare workers for whom the hand cleaning product may be irritating or otherwise unpleasant.
Workflow issues may also be barriers and the impression (perceived or real) that hand washing will slow you down is a frequent barrier.
But, much like described in the Squires study, people often simply forget to wash or are distracted and staff fail to remind each other about hand hygiene. Education is often inadequate. Many still have the mistaken impression that there is no need for hand hygiene of they are wearing gloves. Most importantly, the safety culture (or lack thereof) of the organization is an overriding factor. In many columns of our columns we’ve discussed how safety culture may vary considerably by unit (that’s why improvement projects work best when using the CUSP or comprehensive unit-based safety program model). So even though hand hygiene must be an organization-wide priority you may need to tailor your individual interventions to specific units.
Recommendations (from the Chassin paper and the project website) were nicely summarized into the “HANDS” acronym:
A Active feedback
N No one excused
Making handwashing a habit and automatic is key. Healthcare workers should always wash in and wash out upon entering/exiting a patient care area and before and after patient care.
In addition to providing education, training, and visible and technology-based reminders, one of the most important methods for active feedback was use of “just-in-time” coaching. These individuals, upon observing an episode of noncompliance with hand hygiene, would immediately discuss with the “offender” and find out the reason(s) why they did not perform hand hygiene. Discipline-specific training and education may be important for some issues, such as glove-related problems. And when you use visible and technology-based reminders, make sure you rotate them so that they remain effective and don’t simply get lost in the background “noise”.
“No one excused” means no one is excused. We all know that physicians generally have much poorer compliance with hand hygiene than nurses and other healthcare workers. It is incumbent upon the hospital and physician leadership to make hand hygiene a priority. That holding everyone accountable and responsible and applying progressive discipline from the top. It emphasizes the importance of role models. As we noted above, if you see the leader of a team of rounding physicians and students stop to wash his/her hands, the rest of the team members almost always do the same.
Being data-driven means that you use an acceptable, accurate monitoring and measurement system and provide the data in as near real-time as possible. It also means you scrutinize the data and act upon it.
Fixing the systems, not just the people, is critical. That means providing easy access to hand hygiene equipment and supplies at places the healthcare workers need them. It also means keeping hand dispensers filled. But it is more than that. One of the barriers often noted is that the healthcare worker has his/her hands full and no place to put things down so they can wash their hands. So it means making sure space is available to put those things down. You should also re-engineer the space to minimize the number of times you need to exit and re-enter a room (eg. keep frequently needed supplies in the room so you don’t have to go out and come back in). They also note that your alarm management initiatives (see our July 2, 2013 Patient Safety Tip of the Week “Issues in Alarm Management” and our multiple other columns on alarm-related issues) should reduce the frequency of false alarms that cause your staff to needlessly exit the room. Also, improving the systems by using new technologies like radiofrequency identification and automated reminders and real-time scoring is promising. And placing glove dispensers near the hand dispensers may be important in dealing with the glove-related issues.
The underlying theme of the Chassin paper is that using the Lean, Six Sigma or similar approach allowed each hospital to customize its improvement efforts by focusing on the causes most prevalent at its own facility. “One-size-fits-all” strategies probably won’t work very well.
A third study did qualitative interviews with senior hospital staff at an Australian academic medical center (McInnes 2014). Seven themes emerged: culture change starts with leaders, refresh and renew the message, connect the five moments to the whole patient journey, actionable audit results, empower patients, reconceptualising non-compliance and start using the hammer. Like all other studies they note the importance of leadership not just verbally endorsing good hand hygiene practices but actually demonstrating their commitment and serving as role models. They speak about the hospital hierarchy, whether official or not, that leads to staff not speaking up when they see examples of noncompliance with hand hygiene. They discuss the need to train staff in ways to tactfully address the issue with noncompliers, including use of “graded assertiveness”. Refreshing the message, as noted by many others, is a strategy taken from the advertising and marketing industry. Just like advertising posters get changed at the local bus stop, hospital posters etc. need to be refreshed so that people notice them. They then note that WHO’s “5 Moments of Hand Hygiene” don’t all apply to all settings in the hospital. So there is a need to tailor strategies to individual settings. For example, they note that a group rehabilitation setting is much different than an inpatient bedside setting. Audits need to be actionable. All too often they are neither timely nor specific enough for actions. They recommend deaggregating data so that managers and department heads can take actions with specific groups or individuals. They discuss barriers to empowering patients and the multiple reasons patients won’t speak up. However, they also stress the need to educate staff and physicians on how to respond when a patient does speak up. The last 2 themes, reconceptualising non-compliance and start using the hammer, are related. Many of those interviewed felt that hand hygiene noncompliance needs to be treated as an error and that those making such errors need to be held accountable. Using a graded/staged or tiered approach to managing noncompliant staff (eg. progressive discipline) was felt to be the best approach. Yet many felt that such an approach was counter to the “no blame” culture and also could aggravate a shortage of staff and physicians. All agreed that a multimodal approach to behavior change is much more efficacious than single interventions.
And the fourth study comes from the Pennsylvania Patient Safety Authority (Bradley 2014). Examples of events related to hand hygiene compliance are provided and there are good summaries of the efficacy of alcohol-based handrubs and currently available methods of monitoring compliance. Then the author discusses components of a multimodal approach that begins with assessing barriers to hand hygiene and surveying hand hygiene beliefs and behaviors. It provides links to several useful online tools for those assessments, such as the WHO Hand Hygiene Self-Assessment Framework 2010 and the WHO Perception Survey for Health Care Workers. It goes on to suggest implementation of a hand hygiene “bundle” and map specific strategies to barriers, beliefs and behaviors found in the assessments and suggests a graduated intervention scale called the “disruptive behavior pyramid” as a measure to curtail reckless hand hygiene behaviors.
These 4 studies should help you in addressing this long-running problem that continues to plague most hospitals. Also, for those of you who may have missed them in the fall of 2014 there were evidence-based updates on “Strategies to Prevent Healthcare-Associated Infections through Hand Hygiene” (Ellingson 2014) and SHEA’s “A Compendium of Strategies to Prevent Healthcare-associated Infections in Acute care Hospitals: 2014 Updates” (SHEA 2014).
Some of our other columns on handwashing:
January 5, 2010 “How’s Your Hand Hygiene?”
December 28, 2010 “HAI’s: Looking In All The Wrong Places”
May 24, 2011 “Hand Hygiene Resources”
October 2011 “Another Unintended Consequence of Hand Hygiene Device?”
March 2012 “Smile…You’re on Candid Camera”
August 2012 “Anesthesiology and Surgical Infections”
October 2013 “HAI’s: Costs, WHO Hand Hygiene, etc.”
November 18, 2014 “Handwashing Fades at End of Shift, ?Smartwatch to the Rescue”
Burcharth J, Pommergaard H-C, Alamili M, et al. Fra det videnskabelige julenummer: Hver femte kirurg vasker ikke hænder efter toiletbesøg – et etnografisk feltstudie. Ugeskr Læger 2014; 176: V66434
Bernard D. Twenty Percent of Surgeons Didn't Wash Their Hands in Bathroom. Outpatient Surgery Magazine. January 6, 2015
Squires JE, Linklater S, Grimshaw JM, et al. Understanding Practice: Factors That Influence Physician Hand Hygiene Compliance. Infect Control Hosp Epidemiol 2014; 35(12): 1511-1520
Joint Commission Center for Transforming Healthcare. Hand Hygiene Project.
Chassin MR, Mayer C, Nether K. Improving Hand Hygiene at Eight Hospitals in the United States by Targeting Specific Causes of Noncompliance. Joint Commission Journal on Quality and Patient Safety 2015; 41(1): 4-12
McInnes E, Phillips R, Middleton S, Gould D. A Qualitative Study of Senior Hospital Managers' Views on Current and Innovative Strategies to Improve Hand Hygiene. BMC Infect Dis 2014; 14 (611)
Bradley S. A Systems and Behavioral Approach to Improve Hand Hygiene Practice. Pa Patient Saf Advis 2014; 11(4): 163-7
WHO Hand Hygiene Self-Assessment Framework 2010
WHO Perception Survey for Health Care Workers
Ellingson K, Haas JP, Aiello AE, et al. Strategies to Prevent Healthcare-Associated Infections through Hand Hygiene. Infection Control and Hospital Epidemiology 2014; 35(8): 937-960
SHEA (The Society for Healthcare Epidemiology of America). A Compendium of Strategies to Prevent Healthcare-associated Infections in Acute care Hospitals: 2014 Updates. Infection Control and Hospital Epidemiology 2014; 35(S2), September 2014
January 27, 2015
The Golden Hour for Stroke Thrombolysis
Patients with acute ischemic stroke who are candidates for intravenous thrombolytic therapy benefit most when thrombolytic therapy can be accomplished in a more timely fashion. Though the “window” for thrombolytic therapy may be as long as 4.5 hours, those that do best are those who receive thrombolytic therapy within the first 60 minutes from onset of symptoms, termed the “golden hour”. A recent meta-analysis by the Stroke Thrombolysis Trialists' Collaboration showed that the likelihood ratio of a good stroke outcome (modified Rankin score of 0 or 1) was 1.85 when tPA was given within the first hour and decreased to 1.2 when given at 5 hours (Sandercock 2014). Unfortunately, very few patients are actually treated within the golden hour.
Exciting results of an ad hoc subgroup analysis were recently published (Ebinger 2015). The PHANTOM-S study (Prehospital Acute Neurological Treatment and Optimization of Medical Care in Stroke study) was a prospective controlled study conducted in Berlin, Germany, within an established infrastructure for stroke care. A unique aspect of the study was deployment of a specialized ambulance (the stroke emergency mobile unit or STEMO). This was an ambulance fitted with a mobile CT scanner and point-of-care lab testing and manned by a neurologist, paramedic, and radiology technician. The study was randomized not at the patient level but rather by the weeks according to the availability of the STEMO.
The substudy analyzed thrombolytic therapy rates and found use of STEMO increased the percentage of patients receiving thrombolysis within the golden hour, did not increase the risk to the patients’ safety, and was associated with better short-term outcomes. Thrombolysis rates in ischemic stroke were 32.6% when STEMO was deployed compared to 22.0% when conventional care was administered. Among all patients who received thrombolysis, the proportion of golden hour thrombolysis was 6-fold higher after STEMO deployment (31.0% vs. 4.9%). They were also more likely to be discharged home and had lower 7-day and 90-day mortality rates, though the mortality rate differences did not reach statistical significance. Though the study does not yet have long term outcomes, it is very likely that those will also be better in the group receiving STEMO care and “golden hour” thrombolysis.
This is really exciting work but it will likely be several years before emergency systems and hospitals in the US might be prepared to institute STEMO’s and associated equipment, staffing and protocols.
There is one group of patients who theoretically should be ideal for thrombolytic therapy within the golden hour: those patients having a stroke while already an inpatient in the hospital.
But in our March 18, 2014 Patient Safety Tip of the Week “Systems Approach Improving Stroke Care” we noted a study that mentioned times to treatment are often paradoxically increased in patients having in-hospital strokes (Meretoja 2012). And in our September 23, 2014 Patient Safety Tip of the Week “Stroke Thrombolysis: Need to Focus on Imaging-to-Needle Time” we noted a study (Sauser 2014) that had the interesting observation that decisions take longer when the physician has more time available. Those authors also noted prior studies have demonstrated patients with shorter onset-to-arrival (OTA) times often have longer door-to-needle (DTN) times.
A very telling study was recently presented as an abstract at the Canadian Stroke Congress 2014 (Saltman 2014). Researchers assessed data from 11 regional stroke centers in Ontario, Canada and compared 1048 patients who had strokes while already an inpatient to 32,227 patients who had a stroke elsewhere and were brought to the hospital. Time from symptom recognition to CT scan was 4.5 hours on average for those with in-hospital strokes compared to 1.3 hours for patients brought to the emergency department with a stroke. Only 12% of eligible patient with in-hospital strokes received thrombolytic therapy compared to 19% of those from the community. Moreover, of those receiving thrombolytic therapy only 29% of those with in-hospital stroke received thrombolytic therapy within 90 minutes compared to 72% for those admitted from the community. The in-hospital stroke patients had longer lengths of stay, were less likely to be discharged home, and more likely to be discharged to a rehabilitation facility. These held up even after adjustment for variables such as age, sex, vascular comorbidities, stroke severity and type of stroke.
The authors note that in some cases the symptoms and signs of stroke might be masked in patients already admitted (eg. they might be on a ventilator, be sedated, etc.). But they note that, in general, physicians and staff caring for inpatients are less likely than those in the emergency department or prehospital community to be aware of the protocols for urgent care of stroke patients.
The December 2014 AHRQ Web M&M also had a case study of a patient who suffered a stroke 2 days into a hospital admission (Barrett 2014). It has a good discussion on the protocols we use for managing acute ischemic stroke patients. It mentions several of the barriers to timely assessment and management that we’ve previously discussed in our Patient Safety Tips of the Week for November 6, 2012 “Using LEAN to Improve Stroke Care” and March 18, 2014 “Systems Approach Improving Stroke Care” and September 23, 2014 “Stroke Thrombolysis: Need to Focus on Imaging-to-Needle Time”. These include getting timely imaging studies, drawing and getting lab results in an expedited manner, image interpretation, decision making, ordering and preparing tPA, discussion and informed consent with the patient and family, and administering the tPA. In addition, personnel on inpatient services may be more likely to require neurological consultation than emergency physicians well-trained to handle acute strokes. Or the stroke neurologist on-call may be immediately notified by a stroke alert when a patient is coming to the ED but inpatient staff may not know how to trigger that stroke alert.
In an article about integrating quality improvement into CME activities, Eiser and colleagues noted how discussion at an M&M rounds about a stroke occurring in an inpatient led to recognition that not all clinicians were as familiar with the “stroke alert” process as were emergency physicians (Eiser 2013). This led to dissemination of information about the concept of stroke alert and the protocol procedure to all medical staff, with additional communications to resident physicians via residency program directors.
So few eligible patients are in a position to receive thrombolytic therapy for their acute ischemic stroke within the “golden hour”. It is a shame that those who could most likely be managed in that therapeutic time window are slipping through the cracks in our complex medical system. Does your organization have protocols in place to alert the appropriate stroke team and manage patients expediently when they have a stroke while in the hospital? And are your staff (medical, nursing, residents, etc.) aware of those protocols and the need to intervene immediately?
Some of our previous columns on improving stroke care:
November 6, 2012 “Using LEAN to Improve Stroke Care”
March 18, 2014 “Systems Approach Improving Stroke Care”
Septembrer 23, 2014 “Stroke Thrombolysis: Need to Focus on Imaging-to-Needle Time”
Sandercock P, on behalf of the Stroke Thrombolysis Trialists' Collaboration. 9th World Stroke Congress (WSC). Session FC01 (no abstract number). Presented October 23, 2014
As reported in Medscape. Keller DM. Early Thrombolysis Reduces Post-stroke Disability. Medscape November 11, 2014
Ebinger M, Kunz A, Wendt M, et al. Effects of Golden Hour Thrombolysis. A Prehospital Acute Neurological Treatment and Optimization of Medical Care in Stroke (PHANTOM-S) Substudy. JAMA Neurol 2015; 72(1): 25-30
Sauser K, Levine DA, Nickles AV, Reeve MJ. Hospital Variation in Thrombolysis Times Among Patients With Acute Ischemic StrokeThe Contributions of Door-to-Imaging Time and Imaging-to-Needle Time. JAMA Neurol. 2014; 71(9): 1155-1161
Meretoja A, Strbian D, Mustanoja S, et al. Reducing in-hospital delay to 20 minutes in stroke thrombolysis. Neurology 2012; 79: 306–313
Saltman A, et al. Canadian Stroke Congress. Presented October 6, 2014. Abstract 8094
In-Hospital Stroke Patients Wait Longer for Care. as reported in Medscape Oct 09, 2014.
Also reported in Canadian Stroke Congress. Code Stroke on the Ward. Press Release October 6, 2014
Barrett KM. A Stroke of Error. AHRQ Web M&M. December 2014
Eiser AR, McNamee WB, Miller JY. Integrating Quality Improvement Into Continuing Medical Education Activities Within a Community Hospital System. American Journal of Medical Quality 2013; 28(3): 238-242, first published on September 13, 2012
February 3, 2015
CMS Hopes to Reduce Antipsychotics in Dementia
Antipsychotic medications are often used for treating agitation and aggressive behavior in patients with dementia. Use of antipsychotics in patients with dementia has long under fire because of limited efficacy and occurrence of serious adverse effects, such as an increase in stroke and mortality (Corbett 2014). They may also cause sedation, extrapyramidal signs, and some may produce orthostatic hypotension. The latter may all contribute to falls and fractures, as reported recently in patients 65 years and older who were started on an atypical antipsychotic medication as an outpatient (Fraser 2015). That study found that antipsychotic use increased the risk of serious falls by 52% and the risk or nonvertebral osteoporotic fracture by 50% compared to a matched control group, regardless of the specific agent used.
Despite guidelines and warnings against their use, antipsychotics continue to be used often in nursing homes and long-term care settings. In 2012 CMS challenged LTC and SNF facilities to reduce use of antipsychotics by 15% and between the end of 2011 and the end of 2013, the national prevalence of antipsychotic use in long-stay nursing home residents was reduced by 15.1 percent.
So now CMS has announced that the National Partnership to Improve Dementia Care, a public-private coalition of CMS and several other partners, has established a new national goal of reducing the use of antipsychotic medications in long-stay nursing home residents by a further 25 percent by the end of 2015, and 30 percent by the end of 2016 (CMS 2014).
To make sure the initiative does not produce unintended consequence, CMS will review prescriptions of anxiolytics and sedative/hypnotics to make sure nursing homes do not just replace antipsychotics with other drugs. In addition, CMS will review the cases of residents whose antipsychotics are withdrawn to make sure they don’t suffer an unnecessary decline in functional or cognitive status as a nursing home tries to reduce its usage. Note that a previous Cochrane Review (Declercq 2013) showed the evidence suggests that older nursing home residents or outpatients with dementia can be withdrawn from long-term antipsychotics without detrimental effects on their behavior. Caution is required in older nursing home residents with more severe neuropsychiatric symptoms, as two studies suggest these peoples' symptoms might be worse if their antipsychotic medication is withdrawn. Moreover, one study suggested that older people with dementia and psychosis or agitation and a good response to their antipsychotic treatment for several months could relapse after discontinuation of their antipsychotic medication. They recommended that programs that aim to withdraw older nursing home residents from long-term antipsychotics should be incorporated into routine clinical practice, especially if the neuropsychiatric symptoms are not severe.
The Partnership’s larger mission is “to enhance the use of non-pharmacologic approaches and person-centered dementia care practices”.
In a commentary on the new goals Leonard Gellman, MD, a participant in the Partnership announced by CMS, points out that most antipsychotic medications are not actually prescribed by the nursing homes (Frieden 2014). Rather they are often started when the patient is in a hospital and continued upon discharge or they may have been started by the patient’s primary care physician. Once they have been started, facilities and patients’ families are reluctant to discontinue or reduce them.
So how do you go about reducing such inappropriate usage? An excellent article was recently published on using the FOCUS PDSA process to improve antipsychotic medication management in a long-term care facility (Hampton 2014). They started by putting together a performance improvement team with representation of all key stakeholders and asking appropriate questions about what they wanted to improve and how they would know they were improving before they implemented interventions. They identified a list of 16 antipsychotic medications from the Primaris Changing Antipsychotic Thinking (CAT) program and implemented a screening process for all new admissions who are taking one of the medications. The admitting nurse initiates the screen and forwards a form to the advanced practice RN for review and recommendations about medication management. The team reviewed the medications on each of their 6 patient divisions on a regular basis over several PDSA cycles. They explored whether non-pharmacological interventions had been tried and the committee would decide whether to continue the medication, attempt a gradual dose reduction, or discontinue the medication. Recommendations were forwarded to the patient’s healthcare provider, who could agree or disagree with the recommended action. A log book was kept and the committee’s recommendation was put in a form that became part of the patient’s medical record.
Of the four antipsychotics used most frequently, they were able to reduce the amount of Abilify by 34%, Risperdal by 33%, Seroquel by 54%, and Zyprexa by 27%.
A key barrier identified by Hampton and colleagues was staff concern that undesirable behaviors would emerge in patients as the dose of antipsychotics was reduced. The team therefore looked to CMS’s Hand in Hand program. That is a program that helps nursing homes understand that behaviors are really a form of communication and helps staff learn how to communicate differently with patients and use alternative non-pharmacologic means of dealing with behaviors.
It should be noted that the high placebo response rates (40-50%) seen in clinical trials indicate that other factors (good general care, clinical review, treatment of comorbidities, improved social interaction, etc.) have an impact on the behavioral manifestations of dementia (Corbett 2014).
Beyond the non-pharmacological (behavioral) interventions that should be tried as a first line of management of agitation or aggression in patients with dementia, one must always be alert for other underlying medical problems. Appearance of agitation or other change in behavior in patients with dementia should always prompt a search for possible triggers, such as pain or conditions such as constipation or UTI.
In addition to the beneficial effect on patient safety, such reductions in antipsychotic use should also produce considerable financial savings. In 2011, Medicare Part D spending on antipsychotic drugs totaled $7.6 billion, which was the second highest class of drugs, accounting for 8.4 percent of Part D spending (CMS 2014).
Antipsychotics, of course, are not the only medication commonly misused in dementia patients in nursing homes. Sedatives and hypnotics and antianxiety agents are also commonly misused and will be monitored in the CMS/Partnership initiative as well. And in advanced dementia several other medications of questionable benefit are often continued. A recent study of nursing home patients with advanced dementia found that 53.9% of such patients were prescribed at least one medication of questionable value (Tjia 2014). Cholinesterase inhibitors (36.4%), memantine (25.2%), and lipid lowering agents (22.4%) were most commonly prescribed. High facility use of feeding tubes increased the likelihood of patients receiving such medications. The mean 90-day expenditure for such medications was $816. So we anticipate that as SNF and LTC facilities successfully implement programs to reduce inappropriate use of antipsychotics, sedatives, hypnotics and antianxiety agents, they may look at adding more comprehensive medication management reviews to their activities.
It’s great when we can implement programs that improve patient outcomes and patient safety and reduce costs at the same time!
Corbett A, Burns A, Ballard C. Don’t use antipsychotics routinely to treat agitation and aggression in people with dementia. BMJ 2014; 349 doi: http://dx.doi.org/10.1136/bmj.g6420 (Published 03 November 2014)
Fraser L-A, Liu K, Naylor KL, et al. Falls and Fractures With Atypical Antipsychotic Medication Use: A Population-Based Cohort Study. Research Letter. JAMA Intern Med 2015; Published online January 12, 2015
CMS. National Partnership to Improve Dementia Care exceeds goal to reduce use of antipsychotic medications in nursing homes: CMS announces new goal. CMS Press Release September 19, 2014
Declercq T, Petrovic M, Azermai M, et al. Withdrawal versus continuation of chronic antipsychotic drugs for behavioural and psychological symptoms in older people with dementia. Cochrane Database Syst Rev 2013; 3: CD007726
Frieden J. Antipsychotics for Dementia: CMS Says Use Less. Medpagetoday 2014; September 22, 2014
Hampton JK; Reiter T, Hogarth J, et al. Using FOCUS PDSA to Improve Antipsychotic Medication Management. Journal of Nursing Care Quality 2014; 29(4): 295-302
Primaris. Resources. Changing Antipsychotic Thinking (CAT).
CMS. Hand in Hand: A Training Series for Nursing Homes.
Tjia J, Briesacher BA, Peterson D, et al. Use of Medications of Questionable Benefit in Advanced Dementia. JAMA Intern Med 2014; 174(11): 1763-1771
February 10, 2015
The Anticholinergic Burden and Dementia
Anticholinergic drugs commonly contribute to falls, cognitive impairment, and delirium in the elderly. In addition, peripheral anticholinergic effects may cause dry mouth, blurred vision, exacerbation of glaucoma, constipation, urinary retention or difficulty with micturition, and other side effects. Therefore these drugs often appear on lists of drugs to avoid in the elderly, such as Beers’ List and the STOPP tool (see list of our prior columns on inappropriate prescribing in the elderly at the end of today’s column).
Now a new study used computerized pharmacy dispensing data from a large health plan to assess the impact of cumulative anticholinergic drugs on the development of dementia (Gray 2015). They looked at a cohort age 65 and older (who had no cognitive impairment at the index evaluation) over a 10 year period and found there was a dose-response relationship between use of strong anticholinergic drugs and the development of dementia and Alzheimer’s Disease. The most commonly prescribed categories were tricyclic antidepressants, first-generation antihistamines, and bladder antimuscarinic drugs. Those patients in the highest exposure category had a 54% higher risk of developing dementia (63% higher risk for Alzheimer’s specifically). Moreover, sensitivity analyses showed that the effect was not dependent upon the class of drug (i.e. the effect was present whether the predominant medications were antihistamines or bladder antimuscarinics rather than just antidepressants).
Keep in mind that this was a retrospective analysis and it is almost impossible to rule out confounding factors, such as the reasons the various drugs were prescribed. And such associations don’t necessarily mean cause and effect. Nevertheless, this gives us one more reason to question whether continued use of various drugs with anticholinergic effects is in the individual patient’s best interest.
The Gray study assessed the impact of drugs with strong anticholinergic potency. It used drugs taken from the updated Beers’ List of potentially inappropriate drugs (see our November 12, 2013 Patient Safety Tip of the Week “More on Inappropriate Meds in the Elderly”).
However, another timely study from Australia (Parkinson 2015) assessed the “anticholinergic burden” in women born in 1921-1926 and found that almost 60% used at least one medication with anticholinergic properties. But the most salient finding in that study was that high anticholinergic burden, as measured by the Anticholinergic Drug Scale (Carnahan 2006), was driven not by high potency medications but rather by multiple medications with low anticholinergic potency. We previously noted the risks due to additive effects of multiple medications in our January 28, 2014 Patient Safety Tip of the Week “Is Polypharmacy Always Bad?”. Parkinson et al. note that physicians often readily recognize drugs with high anticholinergic potency but are less likely to recognize when patients are on multiple medications with low anticholinergic potency. Frankly, we were quite surprised at some of the drugs on this list that had some anticholinergic actions (eg. digoxin!, prednisolone!). Also often overlooked are those over-the-counter (OTC) medications that have anticholinergic side effects. Whether the cumulative anticholinergic dose has the same impact on development of dementia as the dose of just high anticholinergic potency medications in the Gray study remains to be seen. However, the potential for an impact of the cumulative dose of all anticholinergic medications on multiple aspects of geriatric care (confusion, delirium, somnolence, falls, etc.) is high.
A previous study (Rudolph 2008) had used Anticholinergic Risk Scale (ARS), a ranked categorical list of commonly prescribed medications with anticholinergic potential. The objective of this study was to determine if the ARS score could be used to predict the risk of anticholinergic adverse effects retrospectively in a geriatric evaluation and management (GEM) cohort and prospectively in a primary care cohort, both of which were predominantly male cohorts. The study showed that higher ARS scores were associated with statistically significantly increased risk of anticholinergic adverse effects in older patients.
There are actually several different tools measuring “anticholinergic burden” and there apparently is not perfect agreement between them (Lertxundi 2013, Lampela 2013). Examples are the Anticholinergic Drug Scale, the Anticholinergic Risk Scale, the Anticholinergic Cognitive Burden Scale, and Chew’s list. Not all the lists include the same drugs and the points given for certain drugs differ among them. But rather than argue about which tool is the best measure of anticholinergic burden, it’s the concept that is important – the anticholinergic effects of multiple medications are additive and, thus, more than one drug may be responsible for detrimental effects.
The editorial accompanying the Gray study (Campbell 2015) discusses the issue of whether the effects of such anticholinergic agents are reversible or not as it pertains to development of dementia. Campbell and Boustani note that it would take a randomized controlled trial of discontinuation of such drugs in a large cohort of patients of substantial duration.
But, risk of dementia aside, we think there are plenty of other reasons to do regular medication reviews on your elderly patients and strongly consider eliminating or reducing the dose of drugs with anticholinergic activity that may not be absolutely necessary.
In a commentary on the Parkinson et al. study in MJA InSight (MacKee 2015), Professor Elizabeth Roughead notes “One of the tricks in prescribing [drugs with anticholinergic effects] is to always note an ‘end-by’ or ‘review-by’ date, so you really have a solid marker for when you should be asking: Can we cease it? Can we lower the dose? Is there an alternative?” Of course, we would argue those flags for review should be used for any medication. But most medications with anticholinergic effects are not life-long medications so it is particularly important that regular review for potential discontinuation or dose reduction be undertaken.
We’ve done several columns now on “deprescribing” (see our Patient Safety Tips of the Week for March 4, 2014 “Evidence-Based Prescribing and Deprescribing in the Elderly” and September 30, 2014 “More on Deprescribing”). We’ve obviously long been big advocates of discontinuing medications which no longer have a positive benefit:harm ratio. And anticholinergic drugs are often on that list of agents whose potential benefits are now exceeded by potential or real harms.
One of the barriers to deprescribing noted in our Patient Safety Tip of the Week for September 30, 2014 “More on Deprescribing” is a reluctance by physicians to discontinue a medication started by another physician, especially those started by a specialist. But one equally big barrier we see is reluctance to discontinue medications that they themselves started. We’ve previously described an initiative in a health system in which physicians were made aware of the potential adverse effects of amitriptyline in their elderly patients. The number of new prescriptions for amitriptyline decreased but almost never did the physicians discontinue amitriptyline they had already prescribed for their patients.
Some of our past columns on Beers’ List and Inappropriate Prescribing in the Elderly:
Gray SL, Anderson ML, Dublin S, et al. Cumulative Use of Strong Anticholinergics and Incident Dementia. A Prospective Cohort Study. JAMA Intern Med 2015; Published online January 26, 2015
The American Geriatrics Society 2012 Beers Criteria Update Expert Panel. American Geriatrics Society Updated Beers Criteria for Potentially Inappropriate Medication Use in Older Adults. J Am Geriatr Soc 2012; 60(4): 616-631
Parkinson L, Magin PJ, Thomson A, et al. Anticholinergic burden in older women: not seeing the wood for the trees? Med J Aust 2015; 202 (2): 91-94
Carnahan RM, Lund BC, Perry PJ, et al. The Anticholinergic Drug Scale as a measure of drug-related anticholinergic burden: associations with serum anticholinergic activity. J Clin Pharmacol 2006; 46(12): 1481-1486
Rudolph JL, Salow MJ, Angelini MC, McGlinchey RE. The Anticholinergic Risk Scale and Anticholinergic Adverse Effects in Older Persons. Arch Intern Med 2008; 168(5): 508-513
Lertxundi U, Domingo-Echaburu S, Hernandez R, et al. Expert-based drug lists to measure anticholinergic burden: similar names, different results. Psychogeriatrics 2013; 13(1): 17–24
Lampela P, Lavikainen, P, Garcia-Horsman JA, et al. Anticholinergic drug use, serum anticholinergic activity, and adverse drug events among older people: a population-based study. Drugs Aging 2013; 30(5): 321-330
Campbell NL, Boustani MA. Adverse Cognitive Effects of Medications. Turning Attention to Reversibility. JAMA Intern Med 2015; Published online January 26, 2015
MacKee N. High anticholinergic burden. MJA InsSight. Monday, 2 February, 2015
Bain KT. Anticholinergic Burden — Tracking Adverse Effects. Aging Well 2011; 4(2): 8
February 17, 2015
Functional Impairment: Hospital Readmission, Surgical Outcomes
It’s been just over 2 years since Harlan Krumholz described the “Post-hospital syndrome—an acquired, transient condition of generalized risk” (Krumholz 2013). He described that recently hospitalized patients experience a period of generalized risk for a range of adverse health events and called this a post-hospital syndrome, “an acquired, transient period of vulnerability”. He suggested that the “the risks in the critical 30-day period after discharge might derive as much from the allostatic and physiological stress that patients experience in the hospital as they do from the lingering effects of the original acute illness”. This state leaves patients vulnerable to readmission, often for conditions different from that of the index hospitalization.
He went on to describe some of the likely factors contributing to this reduction of functional reserve, including metabolic derangements, disturbed sleep patterns, nutritional factors, cognitive factors, pain and other discomforts, etc.
Obviously, there is considerable overlap here with the concept of frailty and reduced physiologic reserves, which we have discussed in many columns (see the full list at the end of today’s column). In addition, functional impairment and functional dependence are related to frailty and are part of the same spectrum. Yet these have generally received much less attention than frailty (other than in the long-term care literature).
Now a new study has looked at the impact of functional impairment, as measured by difficulty with instrumental activities of daily living (IADL) or activities of daily living (ADL), on readmission rates for seniors (Greysen 2015). The researchers found a progressive increase in the adjusted risk of readmission as the degree of functional impairment increased.
Activities of daily living (ADL) include bathing, dressing, transferring, toileting, and eating. Instrumental ADL’s (IADL) require higher levels of functioning and include things like managing finances, shopping, using the phone, taking medications as prescribed, preparing meals, and using transportation.
Greysen and colleagues found a progressive increase in the adjusted risk of readmission as the degree of functional impairment increased: 13.5% with no functional impairment, 14.3% with difficulty with 1 or more instrumental activities of daily living, 14.4% with difficulty with 1 or more ADL, 16.5% with dependency in 1 to 2 ADLs, and 18.2% with dependency in 3 or more ADLs.
Subanalysis for those conditions targeted by Medicare (ie, heart failure, myocardial infarction, and pneumonia) revealed the same trend with larger effects (16.9% readmission rate for no impairment vs 25.7% for dependency in 3 or more ADLs, a 70% increase in risk of readmission).
Many of our columns on frailty have focused on outcomes in patients undergoing surgery. While frailty and functional dependence are two separate entities, they are very much interrelated and part of the same spectrum. Though frailty risk assessments are generally simple, they are not routinely captured on hospitalized patients, whereas functional assessments are often captured (for example, in nursing assessments). Another set of researchers (Scarborough 2015), therefore, looked at functional status and its impact on patients in the ACS-NSQIP database who underwent complex general or vascular operations over a 5-year period. Compared to a propensity-matched cohort, dependent patients had 1.75-fold greater odds of postoperative death than functionally independent patients. They also had a significantly higher incidence of major morbidity (51% higher), failure-to-rescue, and reoperation compared to functionally independent patients. The authors strongly recommend that functional status assessment become a routine part of the preoperative assessment. They note that in some cases the functional impairment might be able to be modified in the preoperative period (eg. through physical therapy). It would also identify a group of patients likely to need additional services postoperatively and at discharge. And it would provide patients and physicians a more realistic expectation of outcomes.
In an editorial accompanying the Scarborough study Robinson and Rosenthal (Robinson 2015), names you’ll recognize from the frailty literature, note that 14 new geriatric focused variables are being collected by 23 NSQIP medical centers in a pilot project. The hope is that these will be used to quantify frailty accurately in older adults and further expand on the already considerable evidence base on the relationship between frailty and surgical outcomes.
Burke and Jha (Burke 2015), commenting on the Greysen study, note that hospitals serving a patient population with more functional dependency will have a more difficult time reducing readmissions. However, they note that functional dependency and preventing declines in functional dependency are obviously very important to patients and their families and would actually be excellent quality metrics for health systems and accountable care organizations.
We’ve long considered assessment for frailty to be one of the three most important components of a good preoperative assessment (the other two being assessments for delirium risk and obstructive sleep apnea). We also mentioned assessment of a patient’s ability to perform activities of daily living in our August 17, 2010 Patient Safety Tip of the Week “Preoperative Consultation – Time to Change”. Given the findings in the current study by Scarborough and colleagues, doing a formal functional assessment before patients are admitted for elective surgery would make a lot of sense. And, for those patients admitted emergently for surgery or admitted to nonsurgical services, doing the functional assessment obviously provides important information about potential extra services the patient may need after acute hospitalization.
We expect we’ll see a lot more in the future about functional dependence, its measurement, and interventions to improve it or prevent deterioration.
Some of our prior columns on frailty:
Krumholz HM. Post-hospital syndrome—an acquired, transient condition of generalized risk. N Engl J Med 2013; 368(2): 100-102
Greysen SR, Cenzer IS, Auerbach AD, Covinsky KE. Functional Impairment and Hospital Readmission in Medicare Seniors. JAMA Intern Med 2015; Published online February 02, 2015
Scarborough JE, Bennett KM, Englum BR, et al. The Impact of Functional Dependency on Outcomes after Complex General and Vasular Surgery. Annals of Surgery 2015; 261(3): 432–437
Robinson TN, Rosenthal RA. Optimizing the Geriatric Preoperative Assessment: The Use of Functional Dependence and Beyond. Annals of Surgery 2015; 261(3): 438–439
Burke LG, Jha AK. Patients’ Functional Status and Hospital Readmissions. Remembering What Matters (Invited Commentary). JAMA Intern Med 2015; Published online February 02, 2015
February 24, 2015
More Risks with Long-Acting Opioids
For quite some time now we have highlighted the dangers of long-acting and/or extended-release opioids (see our Patient Safety Tips of the Week for June 28, 2011 “Long-Acting and Extended-Release Opioid Dangers” and July 24, 2012 “FDA and Extended-Release/Long-Acting Opioids”). Unintentional overdoses with prescription opioids have escalated over the past two decades as prescriptions for all types of opioids have increased. Undoubtedly the development and marketing of multiple opioid preparations has contributed to the increase in prescribing of opioids.
A 2013 CDC report (CDC 2013) showed that fatal overdoses of prescription opioids more than quadrupled between 1999 and 2010 and now exceed fatal overdoses of illicit drugs like heroin and cocaine.
Now a new study further emphasizes the dangers of long-acting opioids in producing unintentional overdoses. Miller and colleagues (Miller 2015) analyzed clinical and pharmacy data from a large VA population over a 10-year period. They identified those patients with non-cancer chronic pain who were newly begun on opioids (having received no opioids for at least the preceding 6 months) and created a propensity-matched cohort for comparison. After adjustment for multiple variables, those patients on long-acting opioids were more than twice as likely to suffer an unintentional overdose than those taking short-acting opioids (hazard ratio 2.33). The risk was especially high during the first two weeks of therapy, where those taking long-acting opioids were more than 5 times more likely to suffer an unintentional overdose. After the first two weeks the risk for unintentional overdose remained twice as high in the group on long-acting opioids. These findings also likely represent an underestimate of the actual occurrence of unintentional overdose.
Opioids in the long-acting group included sustained-release oral morphine sulfate, methadone hydrochloride, controlled-release oxycodone hydrochloride, levorphanol tartrate, and fentanyl patches (they excluded liquid methadone hydrochloride because that is typically used in the VA system for treating opioid addiction).
Though the study had limitations (retrospective design, use of claims database, predominantly male veteran population, inability to exclude unidentified confounders) it nevertheless drives home several important points.
First and foremost is that these long-acting and extended-release opioid formulations are not intended for use as first-line agents in opioid-naïve patients. The newer opiate formulations are either more potent or designed to produce a longer peak action, two characteristics that lead to some of the greatest dangers that have been popping up. We are referring to the long-acting and extended-release forms of opiates. These have been designed to be used in patients who are opioid-tolerant and have pain of a chronic nature that has not been controlled with more conventional opiates. They were not intended to be used for treatment of acute pain nor to be used as first line agents in patients with pain. But in practice they are often being (mis)used in that way.
A second significant factor related to the association between long-acting opioids and overdoses is dosage. The amount of morphine equivalents in these preparations is higher than that found in most short-acting formulations and many prescribers are not appreciative of this. Of course, the issue of dose is not unique to the long-acting opioids. We’ve highlighted the same problem with HYDROmorphone in our September 21, 2010 Patient Safety Tip of the Week “Dilaudid Dangers” and the other columns on HYDROmorphone safety issues listed below. It is also problematic that when switching from short-acting opioids to long-acting or extended-release opioids it is very common to see misunderstandings of the relative potencies of the various opiate preparations.
A third important factor is use of concomitant medications. In the Miller study those patients in the long-acting group were more likely to be also taking benzodiazepines and antidepressants. The increased risk for the long-acting group held up even after adjustments for such variables. However, multiple studies have shown that opioid overdoses, particularly fatal ones, often involve drugs in addition to the opioids. A study of fatal overdoses (Jones 2013) showed many cases had concomitant use of benzodiazepines, antidepressants, antiepileptic agents, antiparkinsonism agents, and antipsychotic or neuroleptic medications. Conversely, fatal overdoses primarily due to these other medications also commonly involved opioids.
Note that long-acting opioid formulations are also now frequent causes of accidental overdoses, including those for whom they were not prescribed such as children and pets (see our September 13, 2011 Patient Safety Tip of the Week “Do You Use Fentanyl Transdermal Patches Safely?” and our May 2012 What’s New in the Patient Safety World column “Another Fentanyl Patch Warning from FDA”).
CPOE (computerized physician order entry) and electronic prescribing probably have the greatest potential to reduce the inappropriate prescribing of long-acting or extended-release opioids. Alerts during CPOE can help prevent their use in opioid-naïve patients and ensure there is a legitimate indication for use of such agents. Similarly, clinical decision support tools during CPOE can help physicians better understand the dosing equivalency issues for each opioid formulation. But we also need to be aware that we do not unintentionally encourage use of such drugs during CPOE. We have seen standardized order sets that have included these formulations as options for pain management for some conditions.
Linking electronic prescribing to prescription databases maintained by state health departments also has great potential to prevent overdoses related to prescription opioids. A study done in Tennessee identified significant risk factors for opioid-related overdose deaths (Gwira Baumblatt 2014). Those risk factors included receiving opioid prescriptions from 4 or more providers, using 4 or more pharmacies, and having a total dose of more than 100 morphine milligram equivalents per day. The authors estimate that about half of the patients could have been identified using these criteria before their deaths.
Our October 2013 What’s New in the Patient Safety World column “Opioid Safety Actions and Resources” provided links to some valuable resources from the FDA, ISMP Canada, SAMHSA, and some state health department resources to help prevent prescription opioid overdoses. The SAMHSA Opioid Overdose Prevention Toolkit includes not only recommendations for physicians regarding opioid prescribing and management but also resources for patients and families, first responders, and community members. It even has resources for survivors of opioid overdose and family members. It has good discussions about recognizing signs and symptoms of opioid overdose and treating overdoses. It also discusses consideration of prescribing a naloxone kit (for emergency treatment of overdose) at the time the opioid prescription is made.
You are probably aware that many communities have begun providing education and naloxone kits to emergency response personnel (eg. police). An observational study in Massachusetts showed that death rates from opioid overdose were reduced in communities where overdose education and naloxone distribution was implemented compared with not implemented (Walley 2013).
The decision to prescribe opioids should not be made without careful consideration of potential risks and benefits and individual patient circumstances. The decision to prescribe long-acting or extended-release opioids requires consideration of even more detailed factors and should not be undertaken lightly.
Our prior articles pertaining to long-acting and/or extended release preparations of opioids:
Our prior columns on patient safety issues related to Dilaudid/HYDROmorphone:
CDC. Addressing prescription drug abuse in the United States: current activities and future opportunities. Atlanta: Centers for Disease Control and Prevention, 2013
Miller M, Barber CW, Leatherman S, et al. Prescription Opioid Duration of Action and the Risk of Unintentional Overdose Among Patients Receiving Opioid Therapy. JAMA Intern Med 2015; Published online February 16, 2015
Jones CM, Mack KA, Paulozzi LJ. Pharmaceutical overdose deaths, United States, 2010. JAMA 2013; 309: 657-659
Gwira Baumblatt JA, Wiedeman C, Dunn JR, et al. High-risk use by patients prescribed opioids for pain and its role in overdose deaths. JAMA Intern Med 2014; 174(5): 796-801
SAMHSA (Substance Abuse & Mental Health Services Administration).
Opioid Overdose Prevention Toolkit. Updated 2014
Walley AY, Xuan Z, Hackman HH, et al. Opioid overdose rates and implementation of overdose education and nasal naloxone distribution in Massachusetts: interrupted time series analysis. BMJ 2013; 346 doi: http://dx.doi.org/10.1136/bmj.f174 (Published 31 January 2013)
March 3, 2015
Factors Related to Postoperative Respiratory Depression
Two of our most frequent topics have been opioid-induced postoperative respiratory depression and perioperative obstructive sleep apnea (OSA). See the extensive list of our prior columns at the end of today’s column. This past month there have been a number of significant articles pertinent to both conditions.
We’ll start with a review of closed claims with postoperative opioid-induced respiratory depression (Lee 2015). The authors searched the Anesthesia Closed Claims Project database between 1990 and 2009 for cases likely to include postoperative opioid-induced respiratory depression. They found 92 probable, possible or definite claims, 77% of which resulted in death or severe brain damage.
Most of the patients were middle aged, obese and had low ASA scores. 16% had OSA diagnosed preoperatively and another 9% were at high risk. Lower extremity orthopedic procedures were overrepresented (41%).
Nearly half received opioids via more than one modality and nearly half were on a continuous opioid infusion at the time of the event. Morphine and fentanyl were the two most commonly administered opioids. A third were also receiving non-opioid sedating medications. Significantly, a third had more than one physician prescribing opioids or other sedating agents. Just as significantly, only 16% were on doses of opioids that the reviewers thought were excessive.
Most events (88%) occurred within 24 hours of the surgical procedure, 13% occurring within 2 hours of transfer from the postoperative recovery room. In 12 of the cases nursing assessments had been done within 15 minutes prior to the event. Importantly, 60% of patients had been described as somnolent, with or without snoring, prior to the event. And reviewers felt that nursing checks were inadequate in at least one respect in 31% of cases. Respiratory monitors and pulse oximetry were in use in less than half, and none of those were on telemetric pulse oximetry. Reviewers felt that 97% of the events were possibly or probably preventable by better monitoring.
Their findings suggest a substantial gap in understanding the signs and symptoms of this opioid-related postoperative phenomenon. In particular, somnolence and snoring were often underappreciated as critical signs of impending respiratory depression. That was a point we noted in our February 12, 2013 Patient Safety Tip of the Week “CDPH: Lessons Learned from PCA Incident”.
It’s hoped that reporting of incidents and near misses of such cases may improve our understanding of all the factors involved in enabling these unfortunate events. The most recent APSF Newsletter discusses the Obstructive Sleep Apnea (OSA) Death and Near Miss Registry, which now accepts case reports (Posner 2015). That article describes what is required in case reports and notes that case report forms and instructions can be downloaded from the registry website.
Following reports on serious complications following tonsillectomy in children (Goldman 2013, Cote 2014) that implicated postoperative respiratory depression and obstructive sleep apnea worsened by opioid therapy, there have been a number of editorials about “the elephant in the room”. Brown and Brouillette (Brown 2014), commenting on the Goldman and Cote and other studies, discussed many of the physiological aspects of respiratory depression and OSA and opioid therapy in children. They note that not only do opioids blunt the ventilator response to hypercarbia and hypoxemia and blunt the arousal responses to OSA but they also note that hypoxemia reduces the dose of narcotics required to alleviate pain in children.
While the Goldman, Cote, and Brown papers dealt with pediatric patients, Benumof (Benumof 2015) noted the bigger problem (the “elephant in the room”) involves all patients undergoing all surgeries. He notes the prototypical “dead in a bed” patient is an obese adult patient with severe OSA receiving opioids postoperatively without continuous electronic monitoring, oxygen supplementation or CPAP. He further calls attention to the creation of the Obstructive Sleep Apnea (OSA) Death and Near Miss Registry mentioned above. Brown and Brouillette, responding to Benumof’s letter, again note that not all cases of OSA are diagnosed before surgery and again mention the McGill Oximetry Score as a potential tool that might be of use in screening (Benumof 2015). That system supplements a careful clinical assessment with home nocturnal pulse oximetry. They acknowledge, however, that the tool needs to be validated in a number of populations.
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”). These highlighted the fact that those patients with CYP2D6 ultrarapid metabolism were especially prone to post-tonsillectomy respiratory depression and suggested that codeine not be used in children undergoing adenotonsillectomy for OSA.
Undoubtedly, the use of codeine after adenotonsillectomy for OSA has diminished significantly after these reports and warnings. However, that does not mean that there has been a switch to safer alternatives. Two recent reports illustrate safety issues that have occurred with use of morphine and tramadol, respectively, in children after adenotonsillectomy for OSA. Kelly and colleagues conducted a prospective randomized clinical trial in children who had sleep disordered breathing who were scheduled for tonsillectomy with or without adenoid removal (Kelly 2015). Children were randomized to receive acetaminophen with either oral morphine or oral ibuprofen. On the first postoperative night oxygen desaturations were improved in 68% of the ibuprofen group vs. only 14% in the morphine group. In fact, the number of desaturation events increased substantially in the morphine group. There were no differences seen in analgesic effectiveness, tonsillar bleeding, or adverse drug reactions. The study was actually terminated early after the interim analysis demonstrated the increased risks with morphine. The authors conclude that ibuprofen in combination with acetaminophen provides safe and effective analgesia in children undergoing tonsillectomy and that post-tonsillectomy morphine use may be unsafe and its use should be limited.
The second paper (Orliaguet 2015) described a 5 year old boy who underwent adenotonsillectomy who received one oral 20mg dose of tramadol and was brought back to the ED the day after surgery with unresponsiveness, pin-point pupils, poor respiration, and oxygen desaturation. He responded dramatically to noninvasive ventilation and intravenous naloxone and fully recovered. CYP2D6 genotyping confirmed the pattern associated with ultrarapid metabolism. Like those in the first paper, the authors suggest use of NSAID’s as an alternative to opioids in children with OSA undergoing tonsillectomy.
Unlike the case in adults, where tools like STOP-BANG are often used to predict OSA, there is no consensus on tools to predict OSA in children. In their study focusing on death and neurological injuries following tonsillectomy Cote et al. 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 (Cote 2014). Those authors stressed 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. In our May 13, 2014 Patient Safety Tip of the Week “Perioperative Sleep Apnea: Human and Financial Impact” we noted screening tools for OSA have been of relatively 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. The McGill Oximetry Score mentioned above (Brown 2014, Benumof 2015) is promising. It has a 97% positive predictive value vs. polysomnography in children and may help identify severity although an inconclusive study does not rule out milder OSA (Brown 2014). But it’s yet to be tested in a randomized, controlled trial. The recently reported CHAT study (Mitchell 2015) identified a number of clinical parameters that correlate with severity of OSA. However, information on demographics, physical findings, and questionnaire responses did not robustly discriminate different levels of OSAS severity.
While we strongly recommend screening for OSA and respiratory risk prior to surgery, it is probably not possible to identify all patients at risk for respiratory depression when exposed to opioids. Therefore, monitoring becomes critical. Our Patient Safety Tips of the Week for February 19, 2013 “Practical Postoperative Pain Management” and May 6, 2014 “Monitoring for Opioid-induced Sedation and Respiratory Depression” discuss many of the important clinical signs and symptoms and use of tools such as the Pasero Opioid-induced Sedation Scale (POSS) and the Richmond Agitation and Sedation Scale (RASS). As above, we need to better educate everyone on recognition of somnolence and snoring as danger signs. But the Lee study (Lee 2015) and numerous anecdotal reports clearly show that episodic vital sign monitoring is grossly inadequate in identifying postoperative respiratory depression. Continuous monitoring is needed. In our March 26, 2013 Patient Safety Tip of the Week “Failure to Recognize Sleep Apnea Before Surgery” we noted that means continuous monitoring of respiratory rate and pattern, oxygenation status, and capnography. Capnography has now become the standard of care for monitoring patients with OSA who are on opioids. As in our February 12, 2013 Patient Safety Tip of the Week “CDPH: Lessons Learned from PCA Incident” sidestream capnography used in unintubated patients may not be particularly good at detecting hypercarbia but is useful in monitoring respiratory rate and detecting apnea. And don’t forget that sedative/hypnotic drugs may also be dangerous in patients with OSA, particularly when used in conjunction with opioids.
Monitoring is probably the most important aspect of care of the patient with suspected OSA and there remain problems with the threshold-based alarm systems most often used today. Lynn and Curry (Lynn 2011) described 3 patterns of unexpected in-hospital deaths (see our February 22, 2011 Patient Safety Tip of the Week “Rethinking Alarms”). The third pattern they describe is one that is typically seen in sleep apnea. In this pattern one sees repetitive reductions in airflow and oxygen saturation during sleep followed by arousals. The arousals rescue the patient but eventually the capacity or reserve of the patient to recover with arousals becomes impaired (often in response to narcotics or sedatives) and the patient may experience sudden death during sleep. The authors discuss the inability of currently used oximeters to recognize this pattern. They even imply that this pattern may give rise to oximeters alarming and being interpreted as “false” alarms attributed to motion artifact, etc. because when staff respond to the alarm the patient is now awake, breathing normally and has a normal oxygen saturation.
The issue of supplemental oxygenation is still much debated. We’ve mentioned on numerous occasions that supplemental use of oxygen may mask impending respiratory depression, particularly in those patients not being monitored with capnography, and may provide a false sense of security.
The issue of perioperative use of CPAP is also still in debate. If a patient has known OSA and has been on CPAP at home, they should get CPAP post-operatively (preferably with their own CPAP equipment brought in from home). But the evidence base for use of CPAP, NIPPV, BiPAP, or APAP in those not previously on CPAP at home is not robust. Our Patient Safety Tips of the Week for September 24, 2013 “Perioperative Use of CPAP in OSA” and May 13, 2014 “Perioperative Sleep Apnea: Human and Financial Impact” suggest that CPAP can be effective in the perioperative period, though compliance with CPAP is suboptimal. Meta-analyses of perioperative use of CPAP in OSA have recently been presented in abstracts at national meetings by the Toronto group that has done so much OSA research. The first suggests that there is a trend toward significance in reducing postoperative adverse events in the CPAP-treated group compared to the non-CPAP group but still acknowledges that further research is needed on the value of perioperative CPAP (Nagappa 2014a). The second (Nagappa 2014b) suggests that perioperative CPAP significantly reduces perioperative AHI (apnea-hypopnea index). Length of stay was not significantly shortened in OSA patients on CPAP undergoing surgery, but this may be due to the small number of patients in the analysis.
Postoperative opioid-induced respiratory depression remains a significant problem and one that is very much preventable. Better recognition of at-risk patients and careful monitoring strategies are needed to prevent this adverse event.
Other Patient Safety Tips of the Week pertaining to opioid-induced respiratory
July 13, 2010 “Postoperative Opioid-Induced Respiratory Depression”
May 12, 2009 “Errors With PCA Pumps”
September 21, 2010 “Dilaudid Dangers”
November 2010 “More on Preoperative Screening for Obstructive Sleep Apnea”
January 4, 2011 “Safer Use of PCA”
February 22, 2011 “Rethinking Alarms”
May 17, 2011 “Opioid-Induced Respiratory Depression – Again!”
September 6, 2011 “More Tips on PCA Safety”
December 6, 2011 “Why You Need to Beware of Oxygen Therapy”
February 21, 2012 “Improving PCA Safety with Capnography”
September 2012 “Joint Commission Sentinel Event Alert on Opioids”
September 2012 “FDA Warning on Codeine Use in Children Following Tonsillectomy”
July 3, 2012 “Recycling an Old Column: Dilaudid Dangers”
February 12, 2013 “CDPH: Lessons Learned from PCA Incident”
February 19, 2013 “Practical Postoperative Pain Management”
Our prior columns on obstructive sleep apnea in the perioperative period:
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”
November 2010 “More on Preoperative Screening for Obstructive Sleep Apnea”
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”
May 13, 2014 “Perioperative Sleep Apnea: Human and Financial Impact”
Lee LA, Caplan RA, Stephens LS, et al. Postoperative Opioid-induced Respiratory Depression: A Closed Claims Analysis. Anesthesiology 2015; 122: 659-665
Posner KL, Bolden N. Obstructive Sleep Apnea Death and Near Miss Registry Opens. APSF Newsletter 2015; 29(3): 53, February 2015
Goldman JL, Baugh RF, Davies L, et al. Mortality and major morbidity after tonsillectomy: Etiologic factors and strategies for prevention. Laryngoscope 2013; 123(10): 2544-2553
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 2014; 118(6): 1276-1283, Published Ahead-of-Print 10 July 2013
Brown KA, Brouillette RT. The Elephant in the Room: Lethal Apnea at Home after Adenotonsillectomy. Anesthesia & Analgesia 2014; 118(6): 1157-1159
Benumof JL. The Elephant in the Room Is Bigger Than You Think: Finding Obstructive Sleep Apnea Patients Dead in Bed Postoperatively. Anesthesia & Analgesia 2015; 120(2): 491, February 2015
Kelly LE, Sommer DD, Ramakrishna J, et al. Morphine or Ibuprofen for Post-Tonsillectomy Analgesia: A Randomized Trial. Pediatrics 2015; 135(2): 307-313 published ahead of print January 26, 201
Orliaguet G, Hamza J, Couloigner V, et al. A Case of Respiratory Depression in a Child with Ultrarapid CYP2D6 Metabolism After Tramadol. Pediatrics 2014; Published online February 2, 2015
Wild D. OSA Screener of Limited Clinical Use in Children, Study Finds. Anesthesiology News 2014; 40:4 April 2014
Mitchell RB, Garetz S, Moore RH, et al. The Use of Clinical Parameters to Predict Obstructive Sleep Apnea Syndrome Severity in ChildrenThe Childhood Adenotonsillectomy (CHAT) Study Randomized Clinical Trial. JAMA Otolaryngol Head Neck Surg 2015; 141(2): 130-136
Lynn LA, Curry JP. Patterns of unexpected in-hospital deaths: a root cause analysis. Patient Safety in Surgery 2011, 5:3 (11 February 2011)
Nagappa M, Wong D, Wong J, Chung F. Effects Of Continuous Positive Airway Pressure On Postoperative Adverse Events In Obstructive Sleep Apnea Patients Undergoing Surgery. A Systematic Review and Meta-Analysis. IARS 2014 Annual Meeting Sessions
Nagappa M, Mokhlesi B, Wong J, et al. Effects of CPAP on Apnea Hypopnea Index & Length of Hospital Stay in OSA Patients Undergoing Surgery: A Meta-analysis. ASA Annual Meeting 2014; Abstract A4012; October 14, 2014
March 10, 2015
FDA Warning Label on Insulin Pens: Is It Enough?
Despite several warnings from ISMP, the FDA, and CDC a series of incidents involving insulin pens being used on multiple patients, potentially causing cross-contamination of patients with blood-borne pathogens, have received considerable attention over the past several years. We discussed them in considerable detail in our February 26, 2013 Patient Safety Tip of the Week “Insulin Pen Re-Use Incidents: How Do You Monitor Alerts?” and our What’s New in the Patient Safety World columns for April 2013 “More Tips on Insulin Pen Safety” and April 2014 “Insulin Pens - Again”.
The FDA has just issued a safety announcement regarding required labeling changes to insulin pens (FDA 2015). The new requirement actually extends to multiple medications for diabetes that are administered by pens or similar devices. The new requirement is that pens and packaging containing multiple doses of insulin and other injectable diabetes medicines display a warning label stating “For single patient use only.”
While that action is an important one and one that should have been implemented long ago, is that enough? We hardly think so. Unless there are interventions that are forcing functions or constraints we are likely to see continued occurrence of these potentially serious incidents.
In our What’s New in the Patient Safety World column for April 2014 “Insulin Pens - Again”) we noted that ISMP had strongly questioned whether hospitals should remove insulin pens from inpatient use all together (ISMP 2013a), a position we would support.
Then in October 2014 ISMP did an eye-opening report where a multihospital system had instituted a series of well-thought-out interventions to help avoid insulin pen errors and monitored their results (ISMP 2014). These best practices included extensive staff education, use of a standardized insulin type (rapid-acting), tape applied to the pen to indicate when it has been used, order-specific barcoding labels and barcode system alerts, reminders and help on eMAR and order entry screens, and a comprehensive monitoring system. They note that overall barcode scanning of the patient, pen, or both occurred in over 99% of insulin doses. But since almost 80,000 insulin doses were given, that meant that mistakes in up to 800 patients could still occur. The rate of near misses averted by barcode scanning was less than 1% but again, given the high number of insulin doses, this amounts to a substantial number of cases that might be occurring in facilities not doing this sort of bar code scanning.
Despite these best practices, insulin pen errors continued to occur. In the 3 months after implementation of these best practices in that multihospital system 7 patients still received an insulin dose using another patient’s pen. Analysis of those cases did not show a knowledge deficit as being contributory. Rather, system errors contributed to the occurrences. For example, using pens from other patients that had not been removed from automated dispensing cabinets or locked patient storage drawers was a factor. Similarly, nurses carrying more than one pen (destined for more than one patient) was a risk factor. You may recall that we recommend you never try to carry medications or equipment for multiple patients at the same time. In our June 19, 2007 Patient Safety Tip of the Week “Unintended Consequences of Technological Solutions” we described an instance where a nurse carrying remote telemetry transmitters for two patients transposed them, resulting in failure to promptly attend to a patient in ventricular fibrillation. And our April 23, 2007 Patient Safety Tip of the Week “Predictable Errors” gave several other examples where the wrong item is chosen when you are carrying “two of something” with you.
Citing this “crack in our best armor” ISMP stopped just short of calling for an “all-out moratorium on using insulin pens in hospitals” but noted it leans toward using them only in special circumstances, such as those that may become available with more concentrated insulin preparations.
Remember, just going back to using insulin vials is also not without some risks. These include concentration issues, look-alike vials, and many other issues. We discussed many of these issues in our November 2, 2010 Patient Safety Tip of the Week “Insulin: Truly a High-Risk Medication” and our July 2014 What’s New in the Patient Safety World column “Joint Commission Sentinel Event Alert: Don’t Misuse Vials”. ISMP also had an excellent prior column on hazards associated with use of insulin vials (ISMP 2013b).
We hope you’ll read through our recommendations in our prior columns on the insulin pen issue (listed below) and the cited ISMP alerts. This is clearly a system issue and requires system fixes. Just attaching a warning to the labels and educating your staff and patients is not going to make this problem go away.
Some of our prior columns highlighting the safety issues of insulin pens and similar devices:
November 2, 2010 “Insulin: Truly a High-Risk Medication”
February 26, 2013 “Insulin Pen Re-Use Incidents: How Do You Monitor Alerts?”
April 2013 “More Tips on Insulin Pen Safety”
April 2014 “Insulin Pens - Again”
FDA. FDA Drug Safety Communication: FDA requires label warnings to prohibit sharing of multi-dose diabetes pen devices among patients. FDA Safety Announcement 2015; February 25, 2015
ISMP (Institute for Safe Medication Practices). Ongoing concern about insulin pen reuse shows hospitals need to consider transitioning away from them. ISMP Medication Safety Alert! Acute Care Edition. February 7, 2013
ISMP (Institute for Safe Medication Practices). A crack in our best armor: “Wrong patient” insulin pen injections alarmingly frequent even with barcode scanning. ISMP Medication Safety Alert! Acute Care Edition 2014; October 23, 2014
ISMP (Institute for Safe Medication Practices). A clinical reminder about the safe use of insulin vials. ISMP Medication Safety Alert! Acute Care Edition 2013; 18(4): 1-4 February 21, 2013
March 17, 2015
Distractions in the OR
Distractions and interruptions are frequent contributing factors to errors in all healthcare settings. In the OR they are especially prone to result in errors that impact patient outcomes. Even short interruptions, especially if they occur during critical parts of procedures or when novel or unexpected events have occurred, could profoundly increase the odds of errors and untoward patient outcomes.
We discussed many aspects related to OR distractions and interruptions in our May 21, 2013 Patient Safety Tip of the Week “Perioperative Distractions”. Interruptions increase the likelihood of errors because we must refocus to resume where we had left off in our task prior to the interruption. It turns out that even very brief interruptions can have a marked impact on our ability to resume those tasks. Altmann and colleagues studied the effect of short interruptions on performance of a task that required participants to maintain their place in a sequence of steps (Altmann 2013). Interruptions averaging just 2.8 s long doubled the rate of sequence errors and interruptions averaging 4.4 s long tripled the rate of sequence errors on post-interruption trials relative to baseline trials.
Another recent study has looked at distractions in the OR (Wheelock 2015). Not surprisingly, distractions occurred in 98% of cases. They occurred at a rate of 10.94 distractions per case or one distraction every 10 minutes.
The most frequent types of distraction were those initiated by external staff entering the operating room. The researchers note that such distractions were unnecessary in 81% of cases! While these researchers actually attributed less significance to their major outcome variables (like teamwork, stress, etc.), they do acknowledge the potential impact on surgical infection rates, which they did not monitor. In several Patient Safety Tips of the Week (“HAI’s: Looking in All the Wrong Places”, “Prolonged Surgical Duration and Time Awareness”, “Operative Duration and Infection”) we’ve noted the risk of infection increases each time the OR door is opened and foot traffic in and out of the OR increases.
Wheelock and colleagues also measured intensity of distractions. They found that the most intense distractions were those that were equipment-related (eg. wrong or missing equipment). Equipment-related distractions impacted all aspects of teamwork and also stress levels for nurses. And such distractions occurred about once every 90 minutes.
Distractions were generally associated with a negative impact on teamwork. Irrelevant conversations had negative influence on coordination and leadership scores for surgeons and anesthesiologists. Such distractions tended to occur more often during periods when workload was low.
Acoustic distractions were associated with higher stress levels for surgeons and higher workload for anesthesiologists. While they did not find a big impact from acoustic distractions, they did note the recent study demonstrating that excessive noise in a pediatric OR was associated with greater levels of surgeon stress and postoperative complications (Engelmann 2014). Also in our May 21, 2013 Patient Safety Tip of the Week “Perioperative Distractions” we noted a study on how background noise in the OR might interfere with surgical team communication (Way 2013). Those researchers found that the impact of noise is considerably greater when the participant is tasked. Moreover, the performance was poorer when the sentences were low in predictability. One can readily see from their results how background noise could interfere with the surgeon’s ability to understand communications during a critical task, particularly if the communication is not a predictable one. The authors conclude that to avoid possible miscommunication in the OR, attempts should be made to reduce ambient noise levels.
Note that the rate of one distraction every 10 minutes seen in the Wheelock study is actually very similar to the rates described in a variety of other healthcare venues and affecting nurses (see our columns August 25, 2009 “Interruptions, Distractions, Inattention…Oops!” and May 4, 2010 “More on the Impact of Interruptions”), ER physicians (March 8, 2011 “Yes, Physicians Get Interrupted Too!”), and radiologists (July 1, 2014 “Interruptions and Radiologists”, November 2014 “More Radiologist Interruptions”). Interestingly, in the Wheelock study distractions had lower frequency in longer cases.
It’s also important to recognize that distractions don’t just apply to the surgical procedure per se. Michelle Feil (Feil 2014), in her excellent article on OR incidents related to distractions in the Pennsylvania PA-PSRS database, notes that almost 20% of the errors were related to laboratory test problems. These included specimen labeling errors, specimen quality problems, and specimen delivery problems.
So what are the strategies that can be employed to minimize the risks due to distractions?
Of course, one way to help ensure that interruptions and distractions do not occur at critical junctures in procedures is use of the “sterile cockpit” concept. In aviation, all extraneous conversations are ceased during preparation for and undertaking takeoffs and landings. That helps ensure all attention is directed to the critical tasks at hand. Hence, the term “sterile cockpit”.
One important consideration, however, is that those critical junctures may differ for different OR team members (Feil 2014). Feil notes several examples of different critical junctures for surgeons, anesthesiologists, nurses, etc. A classic example is the surgical sponge and instrument “count” which requires undivided attention by the nurse(s) and surgical tech(s) who may be doing the count but may not reach the same level of attention by the surgeon and anesthesiologist (even though all should be focused on the count)..
In our May 21, 2013 Patient Safety Tip of the Week “Perioperative Distractions” we noted an editorial by Jacqueline Ross (Ross 2013) pointing out that many distractions and interruptions are likely not preventable but others are preventable. During crucial portions of a procedure (eg. pre-op huddle, surgical timeout, induction, surgical incision, closure, debriefing, anesthesia emergence, etc.) there should be no extraneous conversations and all should focus on the task at hand (Ross 2013). She suggests limiting the number of people entering or leaving the OR during those critical tasks.
Restricting OR traffic
As above, each time the door to the OR opens it introduces an opportunity for not only interruptions and distractions but also increases the potential for a surgical site infection. Restricting OR traffic was one of the two types of interventions Ross had noted as potentially useful in reducing interruptions (Ross 2013). Ross had suggested restricting OR traffic during critical periods that merit a sterile cockpit atmosphere. One might envision setting the OR up like a recording studio with its “On the Air” sign lighting up to restrict entry into the OR during such critical periods. But it makes sense to restrict unnecessary OR traffic whenever possible, not just during critical periods. In the Wheelock study (Wheelock 2015) the most frequent types of distractions were those initiated by external staff entering the operating room and such distractions were unnecessary in 81% of cases! Anecdotally, simply having everyone attempting to enter the OR fill out a log entry with the reason for entering substantially reduces the number of people entering.
The value of preoperative huddles/briefings in avoiding delays and preventing unnecessary interruptions and distractions is immeasurable. The typical preoperative huddle/briefing is done before each case. However, some have used a variant “the daily preoperative huddle” (Jain 2015). In the latter, the team convenes and does the huddle at the start of the day and looks at the entire day’s cases. This gives the team a chance to identify potential problems, set expectations, and develop a shared mental model prior to beginning the day’s cases. Such a huddle works best when the entire team will be present for all the day’s cases. Thus, it really is intended for teams operating within specialty settings. In the Jain study all participants were orthopedic surgeons and the orthopedic teams.
In the pilot study by Jain and colleagues (Jain 2015) the daily huddle resulted in improvement of the surgeons’ perception of the “day’s flow”. The number of unexpected delays dropped from 23% per case to 6.45% per case (and from 79% per day to 21% per day). It also impacted on interruptions, particularly those related to equipment issues, antibiotics, and issues regarding planned procedure. Overall, the number of total interruptions/questions decreased by 77% (from 2.51 per case before implementation of the daily huddle to 0.57 per case after).
As we’ve recommended in our numerous columns on preoperative huddles/briefings Jain and colleagues utilized a structured tool to help identify items to be discussed during the daily preoperative huddle.
Note, however, we suspect the daily huddle concept might be vulnerable to last minute changes in the OR schedule or changes in the schedule that occur after the morning huddle. We’ve seen too many disasters take place when patients are “taken out of turn” in the OR schedule. The “immediate” pre-op huddle is better timed to deal with such contingencies than is the “daily” pre-op huddle. So we would hope that some mechanism would be built in to systems using a daily huddle to add an “immediate” huddle any time an unanticipated change in schedule occurs.
Nevertheless, the concept of the “daily” preoperative huddle is one worth further exploring. We’ve actually advocated for the daily morning huddle in several other venues: the office or clinic, hospitalist rounds, bed coordination rounds, etc. (see our December 9, 2008 Patient Safety Tip of the Week “Huddles in Healthcare”).
Post-operative debriefings are also very helpful at reducing interruptions and delays. Obviously they won’t prevent an interruption in the case just finished but the issues identified can definitely help prevent interruptions in future cases. This is especially likely to be helpful in preventing equipment-related or supply-related issues. Think about how many times you’ve heard after an equipment malfunction “Oh, that happened the last time we used it, too!”. Issues raised in debriefings need to be systematically addressed to provide fixes before they recur (see our July 22, 2014 Patient Safety Tip of the Week “More on Operating Room Briefings and Debriefings”).
Policies on cellphone and other device use
The second area noted by Ross in which distractions might be prevented is use of wireless devices in these areas (Ross 2013). Cellphone use has become ubiquitous. There are many great advantages they provide us. But they also have a downside when used in the OR. Our May 21, 2013 Patient Safety Tip of the Week “Perioperative Distractions” discussed multiple examples of distractions related to cell phones in the OR. There are a multitude of issues related to cell phones in the OR including not only interruptions but also infection control issues, security and confidentiality issues, and detrimental effects on communication in the OR (Byrne 2013). Our recommendation is for all the OR team to leave their cellphones at the main OR desk where someone can triage incoming phone calls (we used to say the same thing for pagers but we haven’t seen a pager in a long time!).
Caregiver distractions from smartphones and other mobile devices even made ECRI Institute’s annual list of Top 10 Technology Hazards for 2013 (ECRI 2012). A recent article in the lay press (Hawryluk 2015) discussed in detail the issue of distractions from smartphones in the OR, highlighting some of the work by anesthesiologist Dr. Peter Papadakos (Papadakos 2011) that we discussed in our May 21, 2013 Patient Safety Tip of the Week “Perioperative Distractions”. The Hawryluk article notes several high profile cases in the press in which distractions occurred in the OR due to personal use of smartphones.
You’ll, of course, get the argument “I use my cellphone to access important information pertinent to the case” (like guidelines, images, reports, etc.). But most of that information can be obtained from devices that do not also send instant messages, texts and phone calls. And if the surgeon really wants to see an imaging study you want him or her looking at it on a large computer screen rather than a small smartphone screen.
Nurses, and perhaps anesthesiologists, are increasingly using mobile devices to improve efficiencies in documentation within the OR and ensuring compliance with guidelines (AORN 2015). But, again, such devices can be configured not to allow distracting features like texting and instant messaging.
Michelle Feil, in addition to her excellent article on OR incidents related to distractions (Feil 2014), had previously researched the PA-PSRS database for events related to distractions in multiple healthcare venues (Feil 2013). She noted that most reports did not note the specific nature of the distraction. Nevertheless, she was able to glean insight from the narrative portion of the reports to provide case examples of the impact of distractions on nursing, surgeons, radiology, laboratory, anesthesia, pharmacy and multiple examples of the impact of distractions on medication errors. She provides a nice description of the constructs involved in memory and the effect of distractions on them. She has a section on sources of distractions that emphasizes “small talk” and technological devices as important sources of distraction.
In both articles, Feil provides multiple strategies to ameliorate the impact of distractions. Those include use of the “sterile cockpit” concept and pre-op huddles/briefings as we’ve discussed above. Others are use of checklists and teamwork training (eg. CRM, TeamSTEPPS™). She emphasizes, however, that having a culture of safety is most important and surgeons must be engaged and take leadership roles in developing that culture in the OR. She goes on to provide a list of risk reduction strategies you should consider implementing. Both the articles by Feil are insightful and useful and we encourage you to read them.
Ironically, most of us don’t even recognize when and how often we are being distracted. There are a couple ways to get a better handle on that, though both are resource-intensive. One is to do the sort of direct observation as done by Wheelock and colleagues. The other is to do video/audio recording in the OR and then play it back for all parties in a constructive fashion so they can see how well (or not so well) they communicated and how distractions interfered with their communications. It can also help assess how well the team adheres to protocols like the Universal Protocol or surgical timeout procedures or the sponge/instrument “count”. But it could be used to assess interruptions and distractions as well. Unfortunately, too many surgeons and hospital attorneys are loathe to use video taping even when it is clearly being done for quality improvement activities.
Prior Patient Safety Tips of the Week dealing with interruptions and distractions:
See our prior columns on huddles, briefings, and debriefings:
Altmann EM, Trafton JG, Hambrick DZ. Momentary Interruptions Can Derail the Train of Thought. Journal of Experimental Psychology: General, Jan 7, 2013
Wheelock A, Suliman A, Wharton RBM, et al. The Impact of Operating Room Distractions on Stress, Workload, and Teamwork. Annals of Surgery 2015; published ahead of print January 23, 2015
Engelmann CR, Neis JP, Kirschbaum C, et al. A noise-reduction program in a pediatric operation theatre is associated with surgeon’s benefits and a reduced rate of complications: a prospective controlled clinical trial. Ann Surg 2014; 259(5): 1025-1033
Way TJ, Long A, Weihing J, et al. Effect of Noise on Auditory Processing in the Operating Room. J Am Coll Surg 2013; 216(5): 933-938
Feil M. Distractions in the Operating Room. Pa Patient Saf Advis 2014; 11(2): 45-52
Ross J. Distractions and Interruptions in the Perianesthesia Environment: A Real Threat to Patient Safety. J Perianesth Nursing 2013; 28(1): 38-39
Jain AL, Jones KC, Simon J, Patterson MD. The impact of a daily pre-operative surgical huddle on interruptions, delays, and surgeon satisfaction in an orthopedic operating room: a prospective study. Patient Safety in Surgery 2015; 9: 8
Byrne MD. Mobile Devices in the Perianesthesia Environment. J Perianesth Nursing 2013; 28(1): 26-30
ECRI Institiute. Top 10 Health Technology Hazards for 2013. Health Devices 41(11): November 2012
Hawryluk M. Is your surgeon focused on you or his smartphone? The Bulletin (Bend, OR) 2015; Published Feb 1, 2015, Updated Feb 2, 2015
Papadakos PJ. Electronic Distraction: An Unmeasured Variable in Modern Medicine. Anesthesiology News 2011; 37:11 November 2011
Association of Perioperative Registered Nurses (AORN) Surgical Conference 2015. Presented March 9, 2015. As reported by Frellick M. Operating Room Best Practices Move to Handheld Devices. Medscape March 09, 2015
Feil M. Distractions and their impact on patient safety. Pa Patient Saf Advis 2013; 10(1): 1-10
Print “Distractions in the OR”
March 24, 2015
Specimen Issues in Prostate Cancer
Imagine getting surgery, radiation or chemotherapy for a condition you really did not have! In our January 22, 2013 Patient Safety Tip of the Week “You Don’t Know What You Don’t Know” we discussed the possibility that you might have a biopsy specimen which was either not yours or was yours but also had some tissue from another patient on the slide(s). Such errors are known as occult specimen provenance complications (SPC’s). In that Tip we noted a study providing an estimate of how often such SPC’s occur (Pfeifer 2013). They examined about 13,000 prostate biopsy specimens from a wide variety of urology practices and pathology laboratories using a DNA identification technology. They found the frequency of occult type 1 errors (a complete transposition between patients) was 0.26% and type 2 errors (contamination of the patient’s tissue with 1 or more unrelated patients) was 0.67%. Overall, the mean frequency of SPCs across practice settings was 0.22% for type 1 errors and 1.69% for type 2 errors.
Basically, it means that around 1% of patients might be given an incorrect diagnosis that no one even suspects is incorrect! Perhaps just as striking is the fact that virtually every lab or clinical setting they studied had at least one SPC identified.
Now a new study in the Journal of Urology has estimated the economic impact of such errors (Wojno 2015). The researchers extracted data from published studies on specimen provenance complications (SPC) rates, prostate cancer treatment efficacy, treatment cost, litigation/settlement costs after false diagnoses of prostate biopsies and patient quality of life. They then estimated how many cases with SPC’s would have their management impacted by the SPC. Note, for example, that a biopsy specimen of a patient with true prostate cancer whose specimen was cross contaminated with that of another patient with prostate cancer would probably not lead to inappropriate treatment of the patient. So they focused on those cases where an SPC would likely have a clinical implication, i.e. those receiving a false positive or false negative diagnosis.
They estimated that approximately 2.5% of the 800,000+ prostate biopsies done in the US annually would involve a specimen switch or contamination overall and that would result in 4,570 clinically meaningful false diagnoses. That would result in an estimated loss of 634 QALY’s and an average cost impact of $3,776 per positive cancer diagnosis. The total estimated impact for the whole country would be $879.9 million annually!
Though no pathology lab was immune to SPC’s in prior studies, rates do vary by site. Sensitivity analyses in this study showed their results were sensitive to the rate of transpositions at independent reference laboratories. Results were also sensitive to litigation/settlement costs.
A bit of concern is the fact that it appears all the authors of the current study have financial ties to a company that does the type of DNA analysis that would need to be done to avoid mistakes related to SPC’s. However, the key previous study (Pfeifer 2013) that identified the SPC problem as widespread did not appear to have such a potential conflict of interest (see our January 22, 2013 Patient Safety Tip of the Week “You Don’t Know What You Don’t Know”). However, we noted there might be some selection bias in that the urology practices submitting specimens for DNA testing may not be representative of all urology practices.
In one of our earliest columns on lab errors (see our October 9, 2007 Patient Safety Tip of the Week “Errors in the Laboratory“) we noted a paper (Suba 2007) that suggested we consider the “DNA timeout” akin to the surgical timeout where we ask the question “Is this the correct diagnosis for the correct patient?” before doing an invasive procedure. One of the co-authors of that 2007 paper subsequently did the study providing an estimate of how often such SPC’s occur (Pfeifer 2013).
The current study looked only a prostate biopsies. It could be anticipated that SPC’s would likely occur with almost any other tissue specimens as well. Application of DNA identification techniques therefore shows promise in reducing the chances a patient may get an incorrect diagnosis and treatment with serious implications. But there important unanswered questions. It needs to be tested in a randomized fashion in a variety of settings with collection of patient-specific outcome data and good analysis of cost (both costs of testing and potential cost savings from reduction of errors) for each of the conditions assessed.
See also our prior columns, listed below, that deal with “lab” errors (most of which do not originate in the lab itself), lost lab specimens, specimen misidentification, labeling issues, and use of FMEA or LEAN techniques to improve safety and efficiency in laboratories.
Some of our other columns on errors related to laboratory studies:
Pfeifer JD, Liu J. Rate of Occult Specimen Provenance Complications in Routine Clinical Practice. Am J Clin Path 2013; 139: 93-100
Wojno K, Hornberger J, Schellhammer P, et al. The Clinical and Economic Implications of Specimen Provenance Complications in Diagnostic Prostate Biopsies. Journal of Urology 2015; Published online: November 13, 2014
Suba EJ, Pfeifer JD, Raab SS. Patient Identification Error Among Prostate Needle Core Biopsy Specimens—Are We Ready for a DNA Time-Out? J Urol 2007; 178(4): 1245-1248
March 31, 2015
Clinical Decision Support for Pneumonia
Last month we had yet another example of a failure of health information technology to improve some facets of care (see our March 2015 What’s New in the Patient Safety World column “CPOE Fails to Catch Prescribing Errors”). We began apologetically noting we’ve had so many columns outlining some of the untoward consequences and other problems with CPOE and healthcare IT in general even though we remain huge supporters of CPOE and clinical decision support and IT applications in healthcare.
Fortunately this month we have a health IT winner! Intermountain Medical Center has recently published a study on the value of a clinical decision support system in reducing mortality for patients with community-acquired pneumonia (Dean 2015). This is a great example of what we’ve long visualized for the utilization of computer support to improve patient outcomes.
Most physicians in emergency departments have long used simple decision support tools like the Pneumonia Severity Index (PSI) or the CURB-65 tool. These have been of some help in decisions about whether a patient with community-acquired pneumonia might be treated as an outpatient or admitted to the hospital (and, if admitted, whether an ICU is indicated). Many hospitals have integrated these tools into their electronic medical record systems or at least attached links to these tools. More often emergency physicians simply use these tools on their smartphones. We find these tools useful but they probably have a limited impact on actual patient outcomes in the big picture.
Intermountain Healthcare really took clinical decision support to the next level. The clinical decision support tool developed at Intermountain lets the computer do work that the busy clinician often does not or cannot take the time to do. Their clinical decision support tool has been described previously (Dean 2013). The IT system culls the patient’s medical record and collects and analyzes data on 40 factors. When it calculates the probability of pneumonia as 40% or higher it notifies the physician. If the physician confirms the diagnosis of pneumonia the CDS tool provides treatment recommendations and recommendations about severity that may help with patient disposition (eg. inpatient, ICU, or outpatient). It makes recommendations about antibiotics as well. For example, the tool looks for risk factors for drug-resistant organisms such as a previous hospital admission or an actual previous culture of a drug-resistant organism. It also looks at where the patient is coming from, such as a long-term care facility which is another risk factor for a drug-resistant organism (the CDS tool apparently even cross references patient addresses with known addresses of long-term care facilities). Thus, the CDS tool may suggest to the clinician that the patient is high risk for a drug-resistant organism in cases where the clinician would not have suspected it. It also provides recommendations about lab tests to identify responsible organisms.
The currently published study (Dean 2015) and the related commentary (Intermountain press release 2015) describe use of the CDS tool and its impact on patient mortality. The study was not a randomized controlled trial. Rather it was a prospective study on almost 5000 pneumonia patients, comparing patient outcomes for 4 emergency departments using the tool vs. 3 emergency departments not using the tool. There was no statistically significant difference for the total pneumonia population in severity-adjusted mortality between intervention and usual care ED’s but that included patients with healthcare-acquired pneumonia as well as community-acquired pneumonia. When the healthcare-acquired pneumonia patients were excluded, there was a statistically significant reduction in mortality in the group using the CDS tool (almost 50% lower mortality).
The CDS tool was developed at Intermountain over several years following use of paper-based pneumonia guidelines that had limited impact. The 40 factors utilized include 6 vital sign variables, 6 laboratory values, 25 nursing assessment variables, the patient’s age, the patient's chief complaint, and findings extracted from the chest imaging report using natural language processing. The team chose a threshold of 40% probability of pneumonia to alert the clinician to balance usefulness against the risk of alert fatigue (Dean 2013). Screening tools that emphasize sensitivity generate lots of alerts, many of which will be false alerts. So they chose to emphasize specificity instead. But the clinicians also have access to the CDS tool via a desktop icon if they wish to use it when the alert had not triggered.
Judging from the comments in the press release the CDS tool is well accepted by the physicians in the emergency departments.
The real value of computers in medicine is that they can grab data from multiple sources and assemble that data in one place where complex calculations and rules can be used to help with diagnosis and management. Few clinicians would be able to spend the time getting all the data from those multiple sources nor be able to remember all the rules and calculations that would be needed. This fine implementation of a clinical decision support system is an outstanding example of the potential value of such systems and it’s great to see how it translates to better patient outcomes.
You can imagine similar CDS tools to help with other conditions. For example, an antidiarrheal agent ordered by a clinician for an inpatient might flag the system to activate a CDS tool that would consider the possibility of a C. diff infection. The tool could search for evidence of prior C. diff infection on a prior hospital stay or check to see if the patient had been at other healthcare facilities where exposure to C. diff is known to occur. Importantly, it can check multiple sources to see if the patient has received antibiotics, the most common risk factor for C. diff, or other risk factors such as use of proton pump inhibitors. Based on the results, the tool could alert the Infection Control team, suggest contact precautions be implemented, and suggest appropriate diagnostic testing. If the patient does have a C. diff infection the tool could also recommend appropriate therapy, including recommendations for recurrent C. diff infection.
This is really good work by Intermountain and reinvigorates our faith that clinical decision support tools will finally make a significant impact on patient safety and patient outcomes.
See some of our other Patient Safety Tip of the Week columns dealing with unintended consequences of technology and other healthcare IT issues:
Dean NC, Jones BE, Jones JP, et al. Impact of an Electronic Clinical Decision Support Tool for Emergency Department Patients with Pneumonia. Annals of Emergency Medicine 2015; Published online: February 26, 2015
Intermountain Medical Center. "New study finds digital clinical decision support tools save lives of pneumonia patients ." Medical News Today. MediLexicon, Intl., 12 Mar. 2015. Web. 15 Mar. 2015.
Dean NC, Jones BE, Ferraro JP, et al. Performance and Utilization of an Emergency Department Electronic Screening Tool for Pneumonia. JAMA Intern Med 2013; 173(8): 699-701
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