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October 20, 2020
More on Post-Operative Risks for Patients with OSA
It’s been over 10 years since our August 17, 2010 Patient Safety Tip of the Week “Preoperative Consultation – Time to Change” in which we recommended screening for obstructive sleep apnea (OSA) as one of the 3 most important preoperative considerations (the other 2 being screening for delirium risk and frailty). OSA is, of course, one of the biggest risk factors for opioid-induced respiratory depression (OIRD), which may occur in both surgical and medical patients. This month there were several key studies published in Anesthesia and Analgesia on OSA in the perioperative period.
The Society of Anesthesia and Sleep Medicine partnered with the Anesthesia Closed Claims Project to create an international registry of unexpected critical events occurring in patients with OSA. Bolden et al. published a comprehensive analysis of 66 cases submitted to the “OSA Death and Near Miss Registry” who had procedures under general anesthesia or combined general plus regional anesthesia (Bolden 2020). Most patients (83%) had a confirmed diagnosis of OSA and the rest had been screened as high risk for OSA. Sixty-five percent of patients died or had brain damage; the remaining 35% experienced other critical events.
Fifty-six percent of events occurred on the hospital ward and 21% occurred at home after discharge. The majority of events occurred within the first 24 postoperative hours. Inadequate respiratory monitoring, no supplemental oxygen, lack of personnel closely observing the patient, and coadministration of sedatives and opioids were all associated with worse outcomes.
Of the events that occurred at home, half occurred within 24 hours of procedure end. Notably, these patients were ASA physical status III or IV, and all had received opioids within 24 hours of the event.
Lack of monitoring was an important contributing factor. Whereas most patients in the PACU, stepdown unit, or ICU were monitored, only 57% on the ward and none at home were monitored. Monitoring consisted of intermittent or continuous pulse oximetry. There were no reports of chest impedance or end-tidal carbon dioxide monitoring (capnography).
52% of the patients were receiving supplemental oxygen at the time of the event. But only 7.5% had a positive airway pressure (PAP) device at the time of the event. Nearly all PACU or ICU/step-down unit events were witnessed, with most ward or at-home cases not witnessed.
Ninety-seven percent received opioids within 24 hours before the event, with a wide MME (morphine milligram equivalent) range (0 to 423 MME, median = 122,). Sedative medications were co-administered with opioids in 62%.
As you’d expect, death or brain damage was less common when the event was witnessed. It was also less common when patients were receiving supplemental oxygen or when patients had respiratory monitoring.
There was no evidence for an association between the outcome and sex, age, body mass index (BMI), ASA physical status, OSA diagnosed versus suspected, presence of cardiovascular or pulmonary comorbidities, or hours between anesthesia end and the event. There was also no evidence for an association between severity of OSA and outcome. There was no evidence for an association between MME and outcome.
There was, however, a strong association of death or brain damage with use of sedatives in addition to opioids compared to patients receiving opioids without sedatives (OR = 4.133).
Timing appears to be very important. The majority of events occurred within the first 24 postoperative hours. Note that a previous systematic review of opioids and OSA (Cozowicz 2018) also found the initial 24 hours after opioid administration appear to be most critical with regard to life-threatening OIRD.
Bolden and colleagues called for special attention to the fact that 21% of these events occurred at home. They stress that, with the trend toward ambulatory rather than inpatient surgery, OSA patients will increasingly have ambulatory surgery and potentially be at risk for catastrophic outcomes after discharge. They also note that, despite use of CPAP, patients may still experience postoperative hypoxic events.
Though they found no statistically significant association between severity of OSA and outcome, they note that lack of an association might be attributed to the small sample size. They cite two large studies which demonstrated that patients with severe OSA had higher risk for postoperative adverse outcomes. They also note the lack of an association between MME and outcome might be attributable to the small sample size.
The Postoperative Vascular Complications in Unrecognized OSA (POSA) study (Chan 2019) was a large, multicenter, prospective observational cohort study designed to evaluate the association between the results of preoperative sleep testing for OSA and 30-day postoperative cardiovascular outcomes among patients undergoing noncardiac surgery. Rates of undiagnosed OSA were high. 37.1% of patients had mild OSA, 19.3% moderate OSA, and 11.2% severe OSA. Postoperative cardiovascular events occurred in 19.3% of patients. Severe OSA was significantly associated with a higher rate of postoperative cardiovascular events (adjusted hazard ratio 2.23) but the associations for mild or moderate OSA did not reach statistical significance.
They found a higher risk for postoperative cardiovascular events with longer duration of postoperative oxygen desaturation less than 80%. No significant association was observed between the type of anesthesia or supplemental oxygen therapy and perioperative outcomes. Somewhat surprisingly, they found no significant association with postoperative opioids.
In an editorial accompanying the Chan study, Auckley and Memtsoudis (Auckley 2019) state “Although the effectiveness of these interventions is poorly studied, some suggested strategies may include enhanced monitoring (oximetry, CO2 monitoring), conservative measures (elevating the head of the bed, avoiding supine sleep position, minimizing opioids), and specific OSA therapies such as the perioperative use of positive airway pressure.”
Since the vast majority of patients with OSA are undiagnosed at the time of surgery, we rely heavily on screening tools to identify patients at high risk for OSA. Multiple screening tools are available, including the ASA Check List, the Berlin Questionnaire, the STOP and STOP-Bang Questionnaires, the BOSTN tool, and the P-SAP Score.
The most frequently used tool is the STOP-Bang questionnaire. Sequin et al. (Seguin 2020) note that STOP-Bang has a high sensitivity at scores ≥3, but its specificity is moderate, particularly for scores of 3-4. So, they prospectively studied 115 surgical patients with preoperative STOP-Bang scores of 3–8. Patients were categorized into 2 subgroups: patients with an intermediate (STOP-Bang 3–4) or a high risk of OSA (STOP-Bang 5–8). Patients had a portable polygraph study at their homes (recording blood oxygen saturation (Spo2), electrocardiogram, movements of the chest and abdomen, and breathing events via a nasal cannula overnight).
After adjustment for age, sex, BMI, history of hypertension, diabetes, and major adverse cardiac and cerebrovascular events, patients with a STOP-Bang score of 5–8 had a significantly higher risk of an apnea-hypopnea index (AHI) >15 than those with a STOP-Bang score of 3–4 (odds ratio 2.9).
They concluded that the STOP-Bang questionnaire detected moderate-to-severe OSA patients when scores reached 5–8. However, STOP-Bang scores of 3–4 and alternative scoring models with specific combinations of factors failed to improve the screening of these patients.
They suggest that using the lower STOP-Bang cutoff may result in unnecessary referrals for sleep studies. As an example, they note that a 55-year old man with a history of hypertension scores a 3 on STOP-Bang, even though he has no OSA symptoms or obesity.
One alternative screening tool we have previously highlighted is the BOSTN tool (see our April 2019 What's New in the Patient Safety World column “New Simple OSA Screening Tool: BOSTN”). Raub et al. (Raub 2020) recently assessed use of the BOSTN score and a perioperative pathway for management of patients with suspected obstructive sleep apnea (OSA) in patients undergoing noncardiac surgery. Their results were somewhat surprising. Patients at high risk of OSA required postoperative mechanical ventilation less frequently and were hospitalized for shorter periods of time, despite higher odds of early post-extubation oxygen desaturation.
Those authors note that some previous studies have shown lower perioperative mortality rates for patients at high risk for OSA but others have shown higher rates. In attempt to explain the seeming paradox that lower mortality rates might be seen, they note that, in OSA, intermittent hypoxia and ischemic preconditioning have been postulated as potential mechanisms underlying the protective effects of obesity on mortality.
Our January 2020 What's New in the Patient Safety World column “Opioids and Apnea: Not Just Surgical Patients” noted that opioid-induced respiratory depression is not just a problem in surgical patients. The OpiatesHF Study (Niroula 2019) showed that a large percentage of inpatients with acute heart failure and sleep disordered breathing received opioids. Among those with an AHI greater than or equal to 10/h, escalation of care occurred in 26% of those who received opiates versus 4% of those who did not.
Khanna et al. (Khanna 2020) recently reported the results of the PRODIGY trial, a prospective, observational trial of blinded continuous capnography and oximetry conducted at 16 sites in the United States, Europe, and Asia aimed at prediction of opioid-induced respiratory depression on inpatient wards. Over 1300 patients on general care floors were receiving parenteral opioids (note: patients enrolled in the US were non-surgical patients and those enrolled elsewhere were postsurgical).
46% had one or more episodes of respiratory depression. Patients with ≥1 episode of respiratory depression were 2.5 times more likely to require some rescue intervention, including activation of a rapid response team. They also experienced 3 days longer mean hospital length of stay, which adds to costs.
A prediction model was developed using 5 independent variables: age ≥60 (in decades), sex, opioid naivety, sleep disorders, and chronic heart failure. The resultant PRODIGY score accurately predicted 74% of patients who would have episodes of respiratory depression and allowed separation of 3 groups (low-, medium-, and high-risk). Patients in the high-risk group by PRODIGY score were >6 times more likely to experience OIRD than the patients in the low-risk group.
The authors suggest that implementation of the PRODIGY score could determine the need for continuous monitoring and may be a first step to reduce the incidence and consequences of respiratory compromise in patients receiving opioids on the general care floor. This could certainly be welcome in those facilities that are resource-poor and cannot afford to do universal continuous monitoring with these modalities.
In the editorial accompanying the Khanna study, Prielipp et al. (Prielipp 2020) note that, although OIRD can occur at any time, the highest incidence has been reported in the first 6–24 postoperative hours and that a majority of fatalities due to OIRD occur at night (midnight to 6 am), underscoring the likely contribution of decreased vigilance and availability of night shift staff. They also note other risk factors for development of OIRD: age >65 years, ASA PS ≥III, presence of OSA, cardiac or neurologic disease, diabetes mellitus, hypertension, use of PCA, concomitant use of sedative drugs, different routes of opioid administration, and multiple prescribers of opioids. They also note that, although OIRD can occur following any surgical procedure, the highest incidence appears to be in orthopedic patients, likely reflecting their older age.
Prielipp et al. acknowledge the potential utility of stratifying such patients by risk. However, they also point out the “sobering statistic” that 26% of patients who experience respiratory depression were not identified.
The Society of Anesthesia and Sleep Medicine has published guidelines on preoperative screening and assessment of adult patients with obstructive sleep apnea (Chung 2016) and the intraoperative management of adult patients with obstructive sleep apnea (Memtsoudis 2018). A recent overview of OSA diagnosis and management (Gottlieb 2020) has limited discussion on OSA patients undergoing surgery. But it does state that patients with known OSA should inform all clinicians involved in their perioperative care, including their surgeon and anesthesiologist, of their OSA diagnosis. It recommends patients using PAP should continue this therapy in the perioperative period and those with known or suspected OSA should be monitored closely during the perioperative period, and the use of opiate analgesics should be minimized or avoided if possible.
Our prior columns on obstructive sleep apnea in the perioperative period and other acute settings:
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 2010 “Obstructive Sleep Apnea in the General Inpatient Population”
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”
March 2012 “Postoperative Complications with Obstructive Sleep Apnea”
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”
June 2013 “Anesthesia Choice for TJR in Sleep Apnea Patients”
September 24, 2013 “Perioperative Use of CPAP in OSA”
May 13, 2014 “Perioperative Sleep Apnea: Human and Financial Impact”
March 3, 2015 “Factors Related to Postoperative Respiratory Depression”
August 18, 2015 “Missing Obstructive Sleep Apnea”
June 7, 2016 “CPAP for Hospitalized Patients at High Risk for OSA”
October 11, 2016 “New Guideline on Preop Screening and Assessment for OSA”
November 21, 2017 “OSA, Oxygen, and Alarm Fatigue”
July 17, 2018 “OSA Screening in Stroke Patients”
April 2019 “New Simple OSA Screening Tool: BOSTN”
January 2020 “Opioids and Apnea: Not Just Surgical Patients”
October 6, 2020 “Successfully Reducing Opioid-Related Adverse Events”
Other Patient Safety Tips of the Week pertaining to opioid-induced respiratory depression and PCA safety:
References:
Bolden N, Posner K, Domino KB, et al. Postoperative Critical Events Associated With Obstructive Sleep Apnea: Results From the Society of Anesthesia and Sleep Medicine Obstructive Sleep Apnea Registry. Anesthesia & Analgesia 2020; 131(4): 1032-1041
Cozowicz C, Chung F, Doufas AG, et al. Opioids for Acute Pain Management in Patients With Obstructive Sleep Apnea: A Systematic Review. Anesthesia & Analgesia 2018; 127(4): 988-1001
Chan MTV, Wang CY, Seet E, et al. Association of Unrecognized Obstructive Sleep Apnea With Postoperative Cardiovascular Events in Patients Undergoing Major Noncardiac Surgery. JAMA 2019; 321(18): 1788-1798
https://jamanetwork.com/journals/jama/fullarticle/2733209
Auckley D, Memtsoudis S. Unrecognized Obstructive Sleep Apnea and Postoperative Cardiovascular Complications: A Wake-up Call. JAMA 2019; 321(18): 1774-1776
https://jamanetwork.com/journals/jama/article-abstract/2733190
Seguin L, Tamisier R, Deletombe B, et al. Preoperative Screening for Obstructive Sleep Apnea Using Alternative Scoring Models of the Sleep Tiredness Observed Pressure-Body Mass Index Age Neck Circumference Gender Questionnaire: An External Validation. Anesthesia & Analgesia 2020; 131(4): 1025-1031
Raub D, Santer P, Nabel S, et al. BOSTN Bundle Intervention for Perioperative Screening and Management of Patients With Suspected Obstructive Sleep Apnea: A Hospital Registry Study, Anesthesia & Analgesia 2020; 130(5): 1415-1424
Niroula A, Garvia V, Rives-Sanchez M, et al. Opiate Use and Escalation of Care in Hospitalized Adults with Acute Heart Failure and Sleep-disordered Breathing (OpiatesHF Study). Ann Am Thorac Soc 2019; 16(9): 1165-1170
https://www.atsjournals.org/doi/abs/10.1513/AnnalsATS.201902-100OC
Khanna AK, Bergese SD, Jungquist CR, et al. on behalf of the PRODIGY Group Collaborators. Prediction of Opioid-Induced Respiratory Depression on Inpatient Wards Using Continuous Capnography and Oximetry: An International Prospective, Observational Trial, Anesthesia & Analgesia 2020; 131(4): 1012-1024
Prielipp, Richard C. MD, MBA, FCCM*; Fulesdi, Bela MD, PhD†; Brull, Sorin J. MD, FCARCSI (Hon)‡ Postoperative Opioid-Induced Respiratory Depression: 3 Steps Forward, Anesthesia & Analgesia: October 2020 - Volume 131 - Issue 4 - p 1007-1011
Chung F, Memtsoudis SG, Ramachandran SK, et al. Society of Anesthesia and Sleep Medicine guidelines on preoperative screening and assessment of adult patients with
obstructive sleep apnea. Anesth Analg 2016; 123: 452-473
Memtsoudis SG, Cozowicz C, Nagappa M, et al. Society of Anesthesia and Sleep Medicine guideline on intraoperative management of adult patients with obstructive sleep apnea. Anesth Analg 2018; 127: 967-987
Gottlieb DJ, Punjabi NM. Diagnosis and Management of Obstructive Sleep Apnea: A Review. JAMA 2020;3 23(14):1389-1400
https://jamanetwork.com/journals/jama/fullarticle/2764461
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October 2020
In September, IHI (Institute for Healthcare Improvement) released “Safer Together: A National Action Plan to Advance Patient Safety”. This report was the culmination of collaboration among 27 national organizations committed to advancing patient safety, with input from all relevant stakeholder groups, including patient and family advocates.
The National Action Plan has 17 recommendations to advance patient safety in 4 categories:
Culture, Leadership, and Governance
Patient and Family Engagement
Workforce Safety
Learning System
From the IHI site you can download the plan plus an implementation resource guide and a self-assessment tool.
The focus on workforce safety is timely, in view of the COVID-19 pandemic, and addresses not only the physical well-being of our healthcare workers but also the psychological and emotional health issues, including burnout.
And, of course, it also emphasizes a need we have long advocated: the need to share lessons learned on a much wider scale.
References:
IHI (Institute for Healthcare Improvement). National Action Plan to Advance Patient Safety. IHI 2020
Print “October 2020 IHI’s National Action Plan to Advance Patient Safety”
We often do talks on the adverse effects of low-value care and how such can lead to the diagnostic cascade and injuries to patients. One of our favorite examples is pre-op testing prior to cataract surgery. Most patients undergoing cataract surgery do not need any pre-op testing because it neither decreases the incidence of perioperative adverse events nor improves cataract surgery outcomes. Yet pre-op testing continues to be surprisingly frequent.
We often cite an article by Ganguli et al. (Ganguli 2019) that care cascades after preoperative EKG for cataract surgery can be costly. Of those who had a pre-op EKG, 15.9% had at least 1 potential cascade event. Those included more tests, cardiology visits, and treatment. Spending for the additional services was up to $565 per Medicare beneficiary, or an estimated $35,025,923 annually across all Medicare beneficiaries in addition to the $3,275,712 paid for the preoperative EKG’s. That study focused on cost and did not assess whether those who had a care cascade suffered any adverse events.
But a new study (Chen 2020) shows yet another unexpected adverse effect of pre-op testing in older patients prior to cataract surgery – falls!
Chen and colleagues looked at data on almost 250,000 Medicare patients. They measured the mean and median number of days between ocular biometry and cataract surgery, calculated the proportion of patients waiting >30 days or >90 days for surgery, and determined the odds of having a fall within 90 days of biometry among patients of high-testing physicians (testing performed in ≥75% of their patients) compared to patients of low-testing physicians.
Falls before cataract surgery in patients of high-testing physicians increased by 43% within the 90 days following ocular biometry (1.0% vs 0.7%). The adjusted odds ratio of falling within 90 days of biometry in patients of high-testing physicians versus low-testing physicians was 1.10 (1.07 after adjusting for surgical wait time). Fall-related hip fractures, other fractures and joint dislocations were also significantly more frequent during the period between biometry and surgery for those patients treated by high-testing physicians.
The delay associated with having a high-testing physician was approximately 8 days (estimate 7.97 days).
Confounding factors cannot be excluded as contributing to the disparity. Patients treated by higher-testing physicians were, on average, slightly older and in poorer health status but Charlson comorbidity index was comparable for the 2 groups. However, the authors found a lack of association between physician testing behavior and falls in the 360 days preceding biometry and felt that supports their hypothesis that falls that occur after a patient begins preparing for surgery are associated with the routine use of preoperative testing, rather than from other underlying differences in patients of high-testing physicians compared to patients of low-testing physicians.
Though the absolute numbers of patient having falls or fall-related injuries during the delay before surgery were low, any such events are unwarranted since the testing is unnecessary. This is probably the first study to document actual detrimental patient outcomes that occur as a result of unnecessary testing in this population. So not only does such unnecessary testing lead to unnecessary cost to the healthcare system, it probably does also result in some degree of patient harm. We also suspect that procedures related to diagnostic cascades following such testing may well also be associated with some degree of patient harm.
This is likely yet another example of “less is more”.
We’ve done several columns (listed below) on the relationship, at times complex and sometimes counterintuitive, between vision problems and falls.
Some of our previous columns on falls after correction of vision:
June 2010 “Seeing Clearly a Common Sense Intervention”
June 2014 “New Glasses and Fall Risk”
August 2014 “Cataract Surgery and Falls”
October 2019 “Visual and Hearing Loss and Medical Costs”
Some of our prior columns related to falls:
References:
Ganguli I, Lupo C, Mainor AJ, et al. Prevalence and Cost of Care Cascades After Low-Value Preoperative Electrocardiogram for Cataract Surgery in Fee-for-Service Medicare Beneficiaries. JAMA Intern Med 2019; 179(9): 1211-1219
https://jamanetwork.com/journals/jamainternalmedicine/fullarticle/2735387
Chen CL, McLeod SD, Lietman TM, et al. Preoperative medical testing and falls in Medicare beneficiaries awaiting cataract surgery. Ophthalmology 2020; Published online September 10, 2020
https://www.aaojournal.org/article/S0161-6420(20)30886-1/fulltext
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We learn a great deal from performing root cause analyses (RCA’s) after various incidents. But one thing many organizations fail to do is to learn to identify themes that are common to multiple incidents. One process to identify such themes is called common cause analysis.
Basically, a common cause analysis involves aggregation of RCA’s and identification of themes common to events found in RCA’s done after the individual events. It often better brings into focus system vulnerabilities that might be downplayed in individual RCA’s. For example, you might identify one or more factors in multiple RCA’s on seemingly unrelated events.
A recent paper showed how one pediatric hospital used common cause analysis of hospital safety events that involve radiology to identify opportunities to improve quality of care and patient safety (Khalatbari 2020). The authors reviewed all RCA’s of incidents involving diagnostic or interventional radiology over a 5+ year period.
From 19 safety events, they identified 64 sequential interactions that were attributed to the radiology department. Of these 19 events, 9 were classified as a serious safety event, 9 as a precursor safety event, and 1 as a known complication. The 9 serious safety events included a delay in diagnosis or treatment (6) or other procedural errors (3). The 9 precursor safety events included a wrong or unnecessary procedure (3), procedural errors (3), delay in diagnosis or treatment (2) and loss of patient data (1). Overall, five diagnostic errors occurred. The two most common system failure modes identified for all 64 sequential interactions were culture (32.8%) and process (21.9%).
Common cause analysis uses Pareto charts to prioritize those factors that occur most often in untoward incidents. It also uses identification of “key processes” (specific sequences of distinct tasks that are essential to the delivery of care and service in the hospital) and “key activities” (distinct tasks that are part of a key process and which may be components of multiple key processes). Some of you may recognize those concepts as being similar to some of the important elements of LEAN.
The authors conclude that common cause analyses of safety events allow for a more robust understanding of system failures and have the potential to generate more specific process improvement strategies to prevent the reoccurrence of similar errors.
We cite this study not so much to highlight their specific findings, especially since the paper is somewhat difficult to read and uses a lot of technical jargon and taxonomies not often used by most of us. Rather, we wish to draw your attention to the potential utility of common cause analysis.
In another paper that may be a bit more clinically relevant to most, Clapper and Crea (Clapper 2010) used common cause analysis to investigate medication errors throughout the system in a large health organization, identify solutions, and reduce adverse events in high-risk medications by 50%.
And, in our September 10, 2013 Patient Safety Tip of the Week “Informed Consent and Wrong Site Surgery” we discussed a paper that performed a common cause analysis after a series of wrong-site surgical events in a US hospital (Mallett 2012). One of the themes they identified was related to documents used in verification. They found that the consents were not always placed in the correct location in the medical record, were not available to be reconciled, did not specify laterality, and were not obtained by the practitioner performing or involved in the procedure. One of their solutions was revision of the consent form to include a legend (right, left, and bilateral) next to where the practitioner writes the name of the procedure to be performed. That provides a visual cue to the practitioner to ensure laterality during the informed consent procedure. Secondly, they implemented a policy that informed consent must be only obtained by the physician/practitioner performing the procedure or by the resident/fellow who will be performing or assisting with the procedure.
Common Cause Analysis (CCA) is another tool to add to your armamentarium for identifying system factors contributing to adverse events. It’s particularly good for identifying factors whose importance you might otherwise underattribute as significant vulnerabilities in your organization.
Some of our prior columns on RCA’s, FMEA’s, response to serious incidents, etc:
July 24, 2007 “Serious Incident Response Checklist”
March 30, 2010 “Publicly Released RCA’s: Everyone Learns from Them”
April 2010 “RCA: Epidural Solution Infused Intravenously”
March 27, 2012 “Action Plan Strength in RCA’s”
March 2014 “FMEA to Avoid Breastmilk Mixups”
July 14, 2015 “NPSF’s RCA2 Guidelines”
July 12, 2016 “Forget Brexit – Brits Bash the RCA!”
May 23, 2017 “Trolling the RCA”
October 2019 “Human Error in Surgical Adverse Events”
January 2020 “ISMP Canada: Change Management to Prevent Recurrences”
References:
Khalatbari H, Menashe SJ, Otto RK, et al. Clarifying radiology’s role in safety events: a 5-year retrospective common cause analysis of safety events at a pediatric hospital. Pediatr Radiol 2020; 50, 1409-1420
https://link.springer.com/article/10.1007%2Fs00247-020-04711-3
Clapper C, Crea K. Common Cause Analysis. Patient Safety & Quality Healthcare 2010; May/June 2010
https://www.psqh.com/analysis/common-cause-analysis/
Mallett R, Conroy M, Saslaw LZ, Moffatt-Bruce S. Preventing Wrong Site, Procedure, and Patient Events Using a Common Cause Analysis. American Journal of Medical Quality 2012; 27: 21-29
https://journals.sagepub.com/doi/pdf/10.1177/1062860611412066
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In our many columns on patient safety issues in the MRI suite, issues related to implants have often been stressed. Certain implants can become heated during MRI scans, they may become dislodged, or they might malfunction.
Analysis of an FDA database revealed over 600 adverse events related to implantable hearing devices during MRI scanning over a 10-year period (Ward 2020a). Most were cochlear implants, but a few were middle ear implants or bone conduction implants and 2 were brainstem implants. The most common cause of the adverse events was dislocation of the magnet in the implantable device, often causing pain. This often leads to premature cessation of the MRI study. In some cases, manufacturer protocols may allow removal of the magnet prior to the MRI but some events occurred even when following manufacturer guidelines. Headbands or splints are recommended by manufacturers in some cases but, even then, adverse events sometimes occurred. Rarely, there was malfunction of the implanted device. Also, implantable devices may lead to artifacts that make interpretation of certain areas difficult.
Thermal burns are the most common adverse MRI event in an FDA database (Forrest 2020a) but most of these are related to superficial devices like coils and EKG leads. Yet even deep implants that have ferromagnetic properties can heat and cause internal thermal injuries. But reassuring was a recent study showing that clinicians can safely perform clinical 3-tesla MRI scans with metal artifact reduction sequence (MARS) protocols on patients with hip arthroplasty implants without excessive thermal heating of the devices (Forrest 2020b). On the other hand, the thermal effects due to the switching of gradient coil (GC) fields on metallic hip implants has been less well studied (Ward 2020b) For the echo-planar imaging (EPI) sequence, which is needed to perform functional MRI and diffusion-tensor imaging, heating is strongly dependent on the position of the body within the scanner The researchers found almost no heating when the implant is at z ≈ 0 from the scanner center, whereas the worst cases occur with z ≈ 300 mm
All the more important that we always ascertain the presence of any implant in a patient prior to undergoing an MRI scan.
Some of our prior columns on patient safety issues related to MRI:
References:
Ward P. Implantable hearing devices cause MRI safety concerns. AuntMinnieEurope.com 2020; August 10, 2020
https://www.auntminnieeurope.com/index.aspx?sec=sup&sub=mri&pag=dis&ItemID=619122
Forrest W, Thermal burns top FDA list of MRI adverse event reports. AuntMinnie.com 2020; August 13, 2020
https://www.auntminnie.com/index.aspx?sec=rca&sub=ismr_2020&pag=dis&ItemID=129887
Forrest W. ARRS: MRI protocols don't affect hip implant temperature. AuntMinnie.com 2020; May 10, 2019
https://www.auntminnie.com/index.aspx?sec=sup&sub=mri&pag=dis&ItemID=125415
Ward P. Caution needed with MRI of patients with metallic implants. AuntMinnie.com 2020; August 13, 2020
https://www.auntminnie.com/index.aspx?sec=rca&sub=ismr_2020&pag=dis&ItemID=129881
Print “October 2020 New Warnings on Implants and MRI”
Print “October 2020 What's New in the Patient Safety World (full column)”
Print “October 2020 IHI’s National Action Plan to Advance Patient Safety”
Print “October 2020 Pre-op Testing Before Cataract Surgery Leads to What?”
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Print “October 2020 New Warnings on Implants and MRI”
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