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June 19, 2018
More EHR-Related Problems
For being long-time advocates of healthcare IT as an important patient safety tool, it sure seems we write a lot about the unintended consequences of that same IT! See the numerous columns listed below for some of the issues we’ve discussed. Some more unintended consequences recently made the medical literature.
One involved a problem arising from use of an order set for acute MI (Gupta 2018). That order set included beginning a beta-blocker, which happened to be contraindicated in the actual patient for whom it was ordered. Its use led to worsening acute heart failure and cardiogenic shock in this patient.
The patient was a 58-year-old man who had a STEMI. He underwent PCI, during which an elevated left ventricular filling pressure was noted. Following the procedure, bradycardia, atrial fibrillation, and complete heart block on the ECG were noted. He was admitted to the coronary care unit and the admitting physician placed orders via the electronic medical record using the "STEMI admission order set". The patient developed worsening shortness of breath, bradycardia (lowest heart rate, 40/min), and hypotension (lowest blood pressure, 93/63 mm Hg), with crackles noted on auscultation of the lung fields consistent with developing cardiogenic shock.
Note that this order set had been developed 5 years earlier and had been reviewed and updated annually. House staff were encouraged to use this “opt in” order set for patients with STEMI. The order set included use of a beta-blocker because such use was originally a performance measure on admission and discharge (the hospital did not change the order set when it had later abandoned that performance measure). Also, though the admission note indicated the physician would withhold beta blockers because of heart failure and complete heart block, the "carvedilol" option on the order set was selected because it was the first and most visible option in the beta-blocker ordering window. The admitting physician also noted he was influenced by the clinical decision support (CDS) message stating that administering beta-blockers was a performance measure.
There were likely also communication errors between the interventional cardiology team and the inpatient cardiology team, resulting in the orders being given before the inpatient team knew all relevant information about the patient.
In the accompanying editorial (Shah 2018) Shah and Cifu note we are often slow to abandon outdated medical practices that are not based upon robust evidence.
Our May 3, 2016 Patient Safety Tip of the Week “Clinical Decision Support Malfunction” highlighted a study from Brigham and Women’s Hospital (BWH) in Boston about some disturbing findings on malfunctions of CDSS alerts (Wright 2016). Alarmingly, they found that the alert malfunctions were often very difficult to detect and some had eluded detection for long periods of time (weeks or even years!). Moreover, the causes for the malfunctions were sometimes even more difficult to elucidate. They were, however, able to identify several contributing factors:
These cases serve as a reminder that you must have a very active multidisciplinary team the oversees your clinical decision support systems (CDSS), even if you contract with an outside vendor for CDSS services. Each time you introduce a new clinical decision rule you need to review its use and impact within several weeks. You are looking primarily to see how often that rule is overridden or ignored and the reasons for that so you can determine whether or not to keep the rule. But once you’ve decided to keep the rule, you need to review it periodically. That should be at least annually and at any time there is a change in the evidence base. The vendors that most hospitals currently contract with for CDSS may issue updates every 6-12 months, but they often do not respond immediately when there is a change in the evidence base that might impact a specific rule. That is why you need to have your own active multidisciplinary team to act when there is a change in the evidence underlying the rule(s). The same applies to order sets. When there is a significant change or new finding in the evidence base, you need to review your standardized order sets that might be impacted by those changes. That means you need to have in place a detailed inventory of items from every order set. For example, let’s say the FDA comes out with a warning about a particular drug. You need to be able to readily identify any of your existing order sets that contain reference to that drug. So you need to have an easily “searchable” library of your order sets.
The Gupta case also highlights the problem that order sets often harbor items that are otherwise hard to detect. A good example of buried items comes from our discussions on inappropriate abbreviations (see our Patient Safety Tips of the Week for July 14, 2009 “Is Your 'Do Not Use' Abbreviations List Adequate?” and December 22, 2015 “The Alberta Abbreviation Safety Toolkit”). In that column we noted we had found pre-existing standardized order sets were a hidden source of many dangerous abbreviations.
In yet another study from Brigham and Women’s Hospital and Partners Healthcare, Wong and colleagues analyzed data on medication-related CDSS overrides in the ICU (Wong 2018). They found the overall appropriateness rate for overrides was 81.6% and varied by alert type. More potential and definite ADE’s (adverse drug events) were identified following inappropriate overrides compared with appropriate overrides (16.5 vs 2.74 per 100 over-ridden alerts). However, inappropriate overrides were over six times as likely to be associated with potential and definite ADE’s, compared with appropriate overrides (OR 6.14). They suggest that further efforts should be targeted efforts such as suppressing alerts that are appropriately over-ridden.
We have echoed the advice of many others that, in order to avoid alert fatigue, you limit the number of alerts your CDSS system triggers for clinicians and focus on those that are most important from a patient safety perspective.
We’ve also often emphasized that it’s important to rout alerts to the person most likely to intervene. That may not always be the physician. Often sending an alert to a pharmacist, who may then intervene with the ordering physician and suggest alternatives, may be the most appropriate routing of some clinical decision rules.
Howe and colleagues (Howe 2018) analyzed patient safety reports from the Pennsylvania Patient Safety Authority database from 2013 through 2016. They found 557 reports (0.03% of all reports) which had language suggesting the EHR potentially contributed to patient harm: potentially required monitoring to prevent harm (84%, n = 468), potentially caused temporary harm (14%, n = 80), potentially caused permanent harm (1%, n = 7), and could have required intervention to save a life or could have resulted in death (<1%, n = 2). They defined 7 categories of “usability factors”, with the following distribution of reports:
Regarding clinical processes, errors occurred during order placement (38%), medication administration (37%), review of results (16%), and documentation (9%).
One potential limitation of the study is that it only included reports which identified one of the top five EHR vendors/products.
Thoughtful design of order entry screens and standardized order sets is important in helping physicians make correct choices and avoid less optimal ones. A recent editorial by Vaughn and Linder (Vaughn 2018) discusses how “nudges” may be helpful. They note some designs provide a stimulus to do the wrong thing. For example, simply providing a checkbox may nudge a physician to check that checkbox. Providing the brandname of a drug may nudge the physician to order the more expensive formulation rather than a generic equivalent. And allowing a test to be ordered repetitively (eg. “daily CBC”) may lead to inappropriate testing.
They suggest the following questions be asked during design of order sets or order entry screens:
They stress the strong effect of using appropriate default settings. They cite a study that successfully reduced inappropriate urine cultures in an emergency room (Munigala 2018) by changing the default option from “urinalysis with reflex to urine culture” to “urinalysis with reflex to microscopy”. (See also our Patient Safety Tips of the Week for July 7, 2009 “Nudge: Small Changes, Big Impact” and February 18, 2018 “Nudged, But Who Nudged Who?” for examples of use of “nudges” in healthcare.)
And the issue of wrong patient events related to the EHR just won’t go away. We’ve discussed this in numerous columns. A 54-year old man died following routine knee surgery due to medications prescribed in the EHR that were intended for a different patient (Minion 2018). An anesthetist in Australia, while attending a new patient in the OR, opened the record of a previous patient to prescribe fluids necessary to “keep the line open” for intravenous antibiotics that had earlier been forgotten. But he forgot to close that patient’s electronic medical record. The anesthetist then prescribed doses of fentanyl meant for the patient currently in the OR but entered these by mistake in the open record of that previous patient. Apparently the HER did present multiple alerts while he was prescribing but all were overridden by the anesthetist, selecting ‘consultant’s decision’ and entering his password each time.
Interestingly, several of the key features of EHR’s that we have previously described (see our May 20, 2008 “CPOE Unintended Consequences – Are Wrong Patient Errors More Common?”) do not seem to have played a role in the error(s) in this case. The patient’s name was apparently displayed on all screens in this case. There was nothing to suggest juxtaposition errors or truncation errors. And it does not appear that two patient records were open at the same time or that 2 different applications were open at the same time. But the last feature we highlighted, failure to log off, was obviously the major problem here. We suspect that interventions such as those developed by Adelman and colleagues, including the ID-verify alert (prompt with name, age, gender and MD must verify) and ID-reentry function (MD must re-enter patient’s initials, age, gender) might have prevented the patient misidentification in the current case (see our August 1, 2017 Patient Safety Tip of the Week “Progress on Wrong Patient Orders”).
Lastly, it’s important to remember that EHR upgrades or conversions from one EHR to another represent times of vulnerability to errors. The Brigham and Women’s Hospital has had one of the most robust and most studied EHR’s from the standpoint of patient safety. Several of our columns (including references above in today’s column) have pointed out how it’s clinical decision support tools and alerts have been fine-tuned to reduce low-impact alerts and help avoid alert fatigue. But recently the system converted from their existing legacy EHR to a commercial EHR and some unintended consequences were found (Wright 2018). Though the knowledge base and content of drug-drug interaction (DDI) alerts was substantially the same between the two systems, the researchers found a striking drop off in the acceptance rates for DDI alerts after the conversion. Overall interruptive DDI alert burden increased by a factor of 6 from the legacy EHR to the commercial EHR. The acceptance rate for the most severe alerts fell from 100 to 8.4%, and from 29.3 to 7.5% for medium severity alerts. After disabling the least severe alerts, total DDI alert burden fell by 50.5%, and acceptance of Tier 1 alerts rose from 9.1 to 12.7%. The researchers felt that the decrease in acceptance rates could not be fully explained by differences in the clinical knowledge base or by alert fatigue associated with increased alert burden. Instead, they felt that workflow factors played an important role. These included timing of alerts in the prescribing process, lack of differentiation of more and less severe alerts, and features of how users interact with alerts.
Information technology remains one of our most important patient safety tools. But there are important lessons learned in all these cases that can help us all avoid unintended consequences of our IT interventions.
See some of our other Patient Safety Tip of the Week columns dealing with unintended consequences of technology and other healthcare IT issues:
References:
Gupta A, Das SR, Pandey A. β-Blockers in Myocardial InfarctionIssues With Standard Admission Order Sets. JAMA 2018; 319(12): 1269-1270
Shah SD, Cifu AS. From Guideline to Order Set to Patient Harm. JAMA 2018; 319(12): 1207-1208
https://jamanetwork.com/journals/jama/article-abstract/2676090?redirect=true
Wright A, Hickman T-T T, McEvoy D, et al. Analysis of clinical decision support system malfunctions: a case series and survey. JAMIA 2016; First published online: 28 March 2016
http://jamia.oxfordjournals.org/content/early/2016/03/28/jamia.ocw005
Wong A, Amato MG, Seger DL, et al. Prospective evaluation of medication-related clinical decision support over-rides in the intensive care unit. BMJ Qual Saf Published Online First: 09 February 2018. doi: 10.1136/bmjqs-2017-007531
http://qualitysafety.bmj.com/content/early/2018/02/09/bmjqs-2017-007531
Howe JL, Adams KT, Hettinger AZ, Ratwani RM. Electronic Health Record Usability Issues and Potential Contribution to Patient Harm. JAMA 2018; 319(12): 1276-1278
https://jamanetwork.com/journals/jama/article-abstract/2676098?redirect=true
Vaughn VM, Linder JA Thoughtless design of the electronic health record drives overuse, but purposeful design can nudge improved patient care. BMJ Qual Saf 2018; Published Online First: 24 March 2018
http://qualitysafety.bmj.com/content/early/2018/03/24/bmjqs-2017-007578
Munigala S, Jackups RR, Poirier RF, et al Impact of order set design on urine culturing practices at an academic medical centre emergency department. BMJ Qual Saf 2018; Published Online First: 20 January 2018
http://qualitysafety.bmj.com/content/early/2018/01/19/bmjqs-2017-006899
Minion L. Electronic prescribing error in month-old EHR responsible for death of NSW man, State Coroner finds. Healthcare IT News 2018; 06 April 2018
Wright, A, Aaron, S, Seger, D. et al. Reduced Effectiveness of Interruptive Drug-Drug Interaction Alerts after Conversion to a Commercial Electronic Health Record. J Gen Intern Med 2018; first online 15 May 2018
https://link.springer.com/article/10.1007%2Fs11606-018-4415-9#citeas
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June 2018
We’ve done many columns on potentially inappropriate medications in the elderly. One class of drugs that always appears on all such lists is benzodiazepines and benzodiazepine receptor agonists. That includes those that are used for promoting sleep, including benzodiazepines, zopiclone, and zolpidem. Such are intended for short-term use but, unfortunately, many patients end up taking them chronically. We’ve described the safety issues associated with these in multiple columns (listed below).
An excellent evidence-based guideline to help clinicians make decisions about when and how to safely taper and stop benzodiazepine receptor agonists was recently published in the journal Canadian Family Physician (Pottie 2018). They note the harms associated benzodiazepine receptor agonists include physical dependence, drowsiness, balance issues, falls, fractures, cognitive impairment, memory disorders (including anterograde amnesia), functional impairment, and motor vehicle accidents. They conducted a systematic review of benzodiazepine receptor agonist (BZRA) deprescribing trials for insomnia, as well as performing a review of the harms of continued BZRA use. The GRADE (Grading of Recommendations Assessment, Development and Evaluation) approach was used for guideline development.
The guideline recommends that deprescribing (tapering slowly) of BZRA’s be offered to elderly adults (≥ 65 years) who take BZRA’s, regardless of duration of use, and suggest that deprescribing (tapering slowly) be offered to adults aged 18 to 64 who have used BZRA’s for more than 4 weeks. Note that the recommendations apply to patients who use BZRA’s to treat insomnia on its own (primary insomnia) or comorbid insomnia where potential underlying comorbidities are effectively managed. It does not apply to those with other sleep disorders or untreated anxiety, depression, or other physical or mental health conditions that might be causing or aggravating insomnia.
The Canadian guideline article also notes the potential financial savings from deprescribing BZRA’s. That includes not just the cost of the drugs themselves but the savings from fewer resultant falls and other adverse patient events.
The guideline comes with an algorithm for deprescribing that includes recommendations about the tapering and need to monitor the patient every 1-2 weeks for the duration of the tapering process. The notes attached to the guideline have a list of the commonly used offending drugs and excellent tips on how to promote sleep non-pharmacologically, both in primary care and institutional settings. It also includes notes about the role of cognitive behavioral therapy (CBT).
The Pottie article also acknowledges the importance of the discussion that needs to take place with patients about deprescribing. Any decision needs to be based on a balance of knowledge about a drug’s indication and effectiveness, as well as risks of use (actual or potential side effects), drug interactions, pill burden, and cost. Decisions also need to take into account patient or family values and preferences as part of shared decision making. The authors note they have developed a patient pamphlet to help with these discussions.
This is a well-referenced and resourced article with excellent recommendations about helping our patients discontinue drugs that may likely have outlasted their temporary benefits but are still putting our patients at risk of many potential adverse consequences.
For more on deprescribing, see our past columns listed below. Also, ISMP Canada (ISMP Canada 2018) recently published a Safety Bulletin that had links to many excellent deprescribing resources that you will find very valuable. One of the linked resources is a toolkit for deprescribing benzodiazepines in older adults put out by Choosing Wisely Canada. Choosing Wisely Canada has also developed several other toolkits for deprescribing other drugs.
Some of our past columns on deprescribing:
Some of our previous columns on safety issues associated with sleep meds:
August 2009 “Bold Experiment: Hospitals Saying No to Sleep Meds”
March 23, 2010 “ISMP Guidelines for Standard Order Sets”
May 2012 “Safety of Hypnotic Drugs”
November 2012 “More on Safety of Sleep Meds”
March 2013 “Sedative/Hypnotics and Falls”
June 2013 “Zolpidem and Emergency Room Visits”
August 6, 2013 “Let Me Sleep!”
June 3, 2014 “More on the Risk of Sedative/Hypnotics”
May 15, 2018 “Helping Inpatients Sleep”
Some of our past columns on Beers’ List and Inappropriate Prescribing in the Elderly:
References:
Pottie K, Thompson W, Davies S, et al. Deprescribing benzodiazepine receptor agonists. Evidence-based clinical practice guideline. Canadian Family Physician 2018; 64(5): 339-351
http://www.cfp.ca/content/64/5/339
ISMP Canada. Deprescribing: Managing Medications to Reduce Polypharmacy. ISMP Canada Safety Bulletin 2018; 18(3): 1-4 March 28, 2018
https://www.ismp-canada.org/download/safetyBulletins/2018/ISMPCSB2018-03-Deprescribing.pdf
Choosing Wisely Canada. DROWSY WITHOUT FEELING LOUSY. A toolkit for reducing inappropriate use of benzodiazepines and sedative-hypnotics among older adults in primary care. July 2017
https://choosingwiselycanada.org/wp-content/uploads/2017/12/CWC-Toolkit-BenzoPrimaryCare-V3.pdf
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We’ve done multiple columns questioning the likely overuse of oxygen and its potential untoward side effects, particularly in patients with stroke or myocardial infarction who are not hypoxemic (see list of those prior columns below).
While many studies have shown lack of benefit of oxygen in patients who are not hypoxemic, only some have suggested that the oxygen supplementation may actually be harmful. Now, a new systematic review and meta-analysis (Chu 2018) concludes that, n acutely ill adults, high-quality evidence shows that liberal oxygen therapy increases mortality without improving other patient-important outcomes. The new review included not only studies of patients with stroke or myocardial infarction but also patients with sepsis, critical illness, trauma, or cardiac arrest, and patients who had emergency surgery. In all, the review included 25 randomized controlled trials with 16,037 total patients.
Compared with a conservative oxygen strategy, a liberal oxygen strategy (median baseline saturation of peripheral oxygen [SpO2] across trials, 96%) increased mortality in-hospital (relative risk 1.21), and at 30 days (RR 1.14), and at longest follow-up (RR 1.10). Morbidity outcomes (disability at longest follow-up, risk of hospital-acquired pneumonia, any hospital-acquired infection, and length of hospital stay) were similar between groups.
They conclude that supplemental oxygen might become unfavorable above an SpO2 range of 94–96% and that these results support the conservative administration of oxygen therapy.
Some of our prior columns on potential harmful effects of oxygen:
April 8, 2008 “Oxygen as a Medication”
January 27, 2009 “Oxygen Therapy: Everything You Wanted to Know and More!”
April 2009 “Nursing Companion to the BTS Oxygen Therapy Guidelines”
October 6, 2009 “Oxygen Safety: More Lessons from the UK”
July 2010 “Cochrane Review: Oxygen in MI”
December 6, 2011 “Why You Need to Beware of Oxygen Therapy”
February 2012 “More Evidence of Harm from Oxygen”
March 2014 “Another Strike Against Hyperoxia”
June 17, 2014 “SO2S Confirms Routine O2 of No Benefit in Stroke”
December 2014 “Oxygen Should Be AVOIDed”
August 11, 2015 “New Oxygen Guidelines: Thoracic Society of Australia and NZ”
November 2016 “Oxygen Tank Monitoring”
November 2016 “More on Safer Use of Oxygen”
October 2017 “End of the Oxygen in MI and Stroke Debate?”
February 2018 “Oxygen Cylinders Back in the News”
References:
Chu DK, Kim L H-Y, Young PJ, et al. Mortality and morbidity in acutely ill adults treated with liberal versus conservative oxygen therapy (IOTA): a systematic review and meta-analysis. Lancet 2018; 391(10131): 1693-1705, Published 28 April 2018
https://www.thelancet.com/journals/lancet/article/PIIS0140-6736(18)30479-3/fulltext
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Among our numerous columns on surgical fires, several have focused on the role of skin preps or ointments as fuels for such fires:
Surgical fires caused by skin preps and ointments also recently was highlighted in an ISMP Medication Safety Alert (ISMP 2018). Over the years, ISMP’s MERP (Medical Error Reporting Program) has noted fires related to a number of substances, mostly flammable substances such as surgical skin preps containing alcohol or alcohol-containing iodophors; eye lubricants and ointments containing petrolatum; wound dressings containing tincture of benzoin or collodion; and skin numbing agents containing ethyl chloride. The latest alert, however, notes some new potentially flammable substances.
Gebauer’s Ethyl Chloride spray, which had been applied as a numbing agent to a patient’s big toe prior to a minor surgical procedure, was ignited when electrocautery was used during the procedure. There are warnings on the bottle, both in the form of a small icon of a flame on the front of the bottle and warning text on the side buried within dense text that it should never be used in the presence of an open flame or electrical cautery equipment. It’s certainly not surprising that such warnings were not heeded.
That is very reminiscent of the easily missed warning we have described in numerous columns about the 26-ml Chloraprep applicator as long ago as 2012 (see, for example, our January 10, 2017 Patient Safety Tip of the Week “The 26-ml Applicator Strikes Again!”). Indeed, the new ISMP report also includes yet another instance related to the 26-ml applicator.
The ISMP article goes on to mention past cases related to Gebauer’s Ethyl Chloride spray, LACRI-LUBE S.O.P. ocular lubricant (white petrolatum and mineral oil ophthalmic ointment), and tincture of benzoin.
As usual, the ISMP alert has excellent recommendations for reducing the risks of surgical fires related to such substances. First is taking inventory of such substances in multiple areas (not just OR’s but any procedural locations, including doctors’ offices, clinics, and ambulatory surgery units). Then the list should be evaluated to see whether safer alternatives are available.
Ensuring awareness of the risks should be a priority. This includes affixing ancillary labeling to the products where the manufacturer’s warnings are “not prominent or distinctive”, as in the case of the 26-ml Chloraprep applicator or the Gebauer’s Ethyl Chloride spray. The also emphasize selection of properly sized prefilled applicators of alcohol-based surgical skin prep solutions.
They also reiterate the other important aspects for prevention of surgical fires, including:
We’ve pointed out in our previous columns that there has been a shift over the years in the “setting” of surgical fires. They now occur more frequently in relatively “minor” surgeries like temporal artery biopsies, or removal of skin lesions or cosmetic procedures on the head/neck region. Two key factors contribute to that trend. One is that in such cases oxygen may be given in a “free” fashion (i.e. it may be delivered via nasal prongs or a face mask rather than via an endotracheal tube or otherwise secured airway). The other factor is a general cavalier attitude when doing “minor” cases and lack of attention to things like the risk of flammable substances as described in today’s column.
Surgical fires are “never events” that are fully preventable. But organizations need to ensure they have raised awareness, done appropriate training, discuss the fire risk during the pre-procedure huddle and/or surgical timeout, and do the things noted above.
Our prior columns on surgical fires:
References:
ISMP (Institute for Safe Medication Practices). Surgical fires caused by skin preps and ointments: Rare but dangerous and preventable. ISMP Medication Safety Alert! Acute Care Edition 2018; March 8, 2018
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We’ve done several columns highlighting the dangers of inaccurate patient weights in the electronic medical record (EMR). The biggest danger is that incorrect weights may lead to over- or under-dosing for medications whose dose is calculated based upon patient weights. And since many such calculations are based upon the weight entered into a single field in the EMR, a single error may be propagated many times.
We came across an interesting study that looked at incorrect weights in the EMR (Chen 2018). While the focus of the study was identifying errors that skewed data trends over time, the findings of the study have potential patient safety implications and potential solutions.
The authors wrote a program using Perl (Strawberry Perl, 5.24.1.1) to calculate the percentage of weight change for all the possible time intervals between measures (not just consecutive ones) for each patient.
After applying the algorithms and conducting a manual review, they found 2638 spurious values from 317,115 weight data points. This suggests that, at minimum, ∼0.8% of all the weight values in this EMR were spurious. By examining each patient record, they found that 1976 of the 10,000 patients (19.8%) had ≥1 spurious value recorded in the observation period.
Types of error:
Single digit error 148 for 178 42.4%
Decimal misplacement 15.63 for 156.3 0.8%
Missing digit error 11 for 191 5.4%
Transposition 137 for 173 4.2%
kg value entered in lbs. 70 for 154 7.1%
lb value multiplied by 2.2 338.8 for 154 5.6%
No clear reason 237 for 185 34.5%
Weights found to be spurious by all 3 of their algorithms and by manual review comprised ∼1% of all the weight recordings. At least one spurious weight occurred in 1 in 5 patient charts over a 10-y period.
When analyzing such weights in the EMR over time, straightforward algorithms can identify and remove them. Such algorithms, however, might not be useful in acutely hospitalized patients unless a whole host of prior weights were available for analysis. Nevertheless, the types of error identified by Chen et al. are informative because they demonstrate the potential for similar erroneous weights to be recorded in the EMR at a time when they could lead to potentially serious over- or under-dosing of medications.
Some of our other columns on errors related to patient weights:
March 23, 2010 “ISMP Guidelines for Standard Order Sets”
September 2010 “NPSA Alert on LMWH Dosing”
August 2, 2011 “Hazards of ePrescribing”
January 2013 “More IT Unintended Conseequences”
December 8, 2015 “Danger of Inaccurate Weights in Stroke Care”
May 2016 “ECRI Institute’s Top 10 Patient Safety Concerns for 2016”
September 2017 “Weight-Based Dosing in Children”
January 2018 “Can We Improve Barcoding?”
References:
Chen S, Banks WA, Sheffrin M, et al. Identifying and categorizing spurious weight data in electronic medical records. The American Journal of Clinical Nutrition 2018; 107(3): 420-426
https://academic.oup.com/ajcn/article/107/3/420/4939337?rss=1
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