Healthcare Consulting Services with a Focus on Patient Safety Solutions and Quality Improvement Across the Health Care Continuum. Your Patient Safety Resource Solution.

Patient Safety Tip of the Week 

May 11, 2021

How Are Alerts in Ambulatory CPOE Doing?

When we did our first CPOE implementation back in 2007, we were flooded with suggestions for potential alerts that could be used for patient safety. We had many ideas for alerts ourselves. But we readily recognized the need to limit such alerts in order to avoid alert fatigue.

Perhaps the prime opportunity to use alerts to drive clinician behavior is in medication safety. Computers can work rapidly in the background to identify issues like allergies, drug-drug interactions, drug-disease contraindications, effects of renal or hepatic dysfunction, and other considerations that should be taken into account when prescribing medications. Most clinicians cannot take the time to consider all those factors when prescribing. So, computer-generated alerts can provide important information to the clinician at the time of order entry.

There are 2 types of alerts: “soft” alerts and “hard” alerts. Soft alerts are suggestions that the clinician can choose to implement or ignore. Hard alerts are ones that require the clinician to do something, such as accept the recommendation or explain why he/she is overriding the alert (or, in the extreme, would prevent the clinician’s action all together). Interruptive alerts are ones that require interruption of a clinician’s workflow to answer questions or input additional information. Hard alerts are examples of interruptive alerts. There are probably also some “soft” alerts that are interruptive (eg. the alert might make the clinician read a long message).

A recent review (Cerqueira 2021) assessed the effectiveness of interruptive medication-prescriber alerts in changing prescriber behavior and improving patient outcomes in ambulatory care settings via computerized provider order entry (CPOE) systems. The authors found that clinician behavior was influenced in the majority of studies, with most noting a positive change. They found that alerts decreased pharmaceutical costs, moved medications toward preferred medications tiers and steered treatments toward evidence-based choices. Importantly, they also decreased prescribing errors.

But they also found that clinician feedback was rarely solicited and, when it was, showed frustration with alerts creating a time delay. Notably, only one of the nine studies in their review reported feedback that was overall ‘positive’. Clinicians often commented that the alerts were inappropriate and intrusive.

Shi et al. (Shi 2021) recently studied barriers to using clinical decision support in ambulatory care. One of the 7 primary barriers they identified was the use of false and disruptive alarms. Another barrier was the requirement to redesign workflow.

Bombarding clinicians with alerts that are inappropriate and interruptive leads to the phenomenon of “alert fatigue” in which clinicians begin to ignore and override most alerts, even those that have the potential to avert unwanted outcomes.

There have been many studies linking clinician burnout to use of electronic medical records (EMR’s). While most relate to the overall time spent on the EMR (see our  May 2021 What's New in the Patient Safety World column “More on Time Spent on the EMR”), frustration with clinical decision support (CDS) systems has been identified as a key factor in leading to clinician burnout. Jankovic and Chen (Jankovic 2020) reviewed articles dealing with aspects of CDS that contribute to burnout and identify key themes for improving the acceptability of CDS to clinicians, with the goal of decreasing said burnout.

In our June 2020 What's New in the Patient Safety World column “EMR and Medication Safety: Better But Not Yet There” we discussed results from the Leapfrog CPOE EHR evaluation tool shows some improvement over time but highlights the persistence of vulnerabilities and the wide variability of hospital CPOE EHR systems to identify medication errors and prevent adverse drug events (ADE’s). Classen et al. (Classen 2020) looked at results from over 2300 hospitals. The overall mean total score increased from 53.9% in 2009 to 65.6% in 2018. The mean hospital score for the “basic” CDS category increased from 69.8% in 2009 to 85.6% in 2018. The mean hospital score for the “advanced” CDS category increased from 29.6% in 2009 to 46.1% in 2018. Hospital EHR’s did better on some categories than others. For example, they did best on the drug-allergy category in each year, increasing from 92.9% in 2009 to 98.4% in 2018. The lowest performing category throughout the study was drug-diagnosis contraindications, where the mean score was only 20.4% in 2009 and 33.2% in 2018. The authors conclude “these systems have only modestly increased their safety performance during a 10-year period, leaving critical deficiencies in these systems to detect and prevent critical safety issues.”

So, why haven’t we been able to use CDS more effectively to improve medication safety and efficacy? It largely boils down to issues related to design and implementation of clinical alerts and reminders.

When the phenomenon of “alert fatigue” became apparent to us, we recognized the need to limit our alerts to those situations we considered most important for patient care. We did the following:

• Established a multidisciplinary committee to assess all suggested alerts and to monitor implemented alerts
• Established monitoring intervals for all implemented alerts (we suggest monitoring at one month, 3 months, and 6 months)
• Monitored the frequency that alerts triggered
• Monitored the alert acceptance and override rates
• Assessed whether the alerts achieved their intended impact
• Looked for any unintended consequences
• Interviewed clinicians to to assess their impression of both the utility and the degree of obtrusiveness of any alerts

Those actions were very much in line with the recommendations the whitepaper “Safe Practices to Reduce CPOE Alert Fatigue through Monitoring, Analysis, and Optimization” from ECRI's Partnership for Health IT Patient Safety (see our March 2021 What's New in the Patient Safety World column “ECRI Partnership Whitepaper on Alert Fatigue”). The ECRI whitepaper (ECRI 2021) actually goes into more detail about the metrics you should be following.

Regarding metrics, one unique metric not mentioned in the ECRI whitepaper but potentially very valuable was described by Einbinder and colleagues (Einbinder 2014): the “number needed to remind” (NNR). Analogous to the number needed to treat (NNT), this is the number of patients reached by a reminder to result in one recommended action being taken. They compared this to the “reminder performance” (RP), which is simply the measure of how often a recommended action is subsequently taken when the reminder is displayed.

Alagiakrishnan et al. (Alagiakrishnan 2019) used the NNR in primary care and geriatric clinics to assess clinical decision support for potentially inappropriate medications (PIM’s) from Beers criteria. Their CDS system used alerts known as Best Practice Advisories (BPA’s) to direct providers to a navigator where orders management, clinical information and educational materials were available. The BPA’s were used to advise clinicians of PIM’s among their patients' medication lists or new orders. The reminder performance (RP) across both clinics was 17.3%, which corresponds to an NNR of 5.8. The reminder performance was 37.1% in geriatric clinics vs. 13.4% in primary care clinics. The NNR in the primary care clinic was 7.4 and NNR in the geriatric clinic was 2.7.

They also developed a metric “Number Needed to Deprescribe” (NND) or the number of alert presentations specific to a medication and patient presented to a physician user before there was a deprescribing event. The reminder performance for deprescribing events was lower at 1.2%. The number needed to deprescribe (NND) was 82, with values for the primary care clinic of 80 and the geriatrics clinic of 96. There was considerable variation in all 3 parameters by the class of medication for which the BPA alerts fired.

The ECRI Partnership whitepaper reiterates the “5 Rights” model of clinical decision support (CDS) adopted from Osheroff et al. (Osheroff 2012):

1. The right information: evidence-based, suitable to guide action, pertinent to the circumstance
2. To the right person: considering all members of the care team, including clinicians, patients, and their caregivers
3. In the right CDS intervention format: such as an alert, order set, or reference information to answer a clinical question
4. Through the right channel: for example, a clinical information system such as an electronic medical record, personal health record, or a more general channel such as the internet or a mobile device
5. At the right time in workflow: for example, at time of decision, action, or need

One of the metrics in the ECRI whitepaper looks at whom the alert is targeted to. That raises a point we’ve often made in the past: you need to target the alert to the individual(s) most likely to get the desired action accomplished. That may not always be the clinician ordering something on CPOE or an ePrescribing system. For example, when an antidiarrheal medication is ordered on a patient receiving antibiotics, an alert to consider C. diff infection might be better targeted to an infection control worker than to the ordering clinician. Or alerts regarding some medication issues might be better targeted to clinical pharmacists.

The ECRI whitepaper also asks one very important question: “Is an alert the appropriate tool?”. Essentially, that is askng whether there is an alternative to accomplish the same goal. We’d like to emphasize that last point. In our March 3, 2009 Patient Safety Tip of the Week “Overriding Alerts…Like Surfin’ the Web” we noted that use of standardized order sets may avoid the need to generate some alerts (though standardized order sets can create some problems of the own, particularly when they contain outdated information that is no longer appropriate).

There is another phenomenon we’ve seen over and over. That is the disparity in effectiveness between “prospective” alerts and “look-back" alerts. When we’ve tried to use alerts to avoid using a “potentially inappropriate” medication (an example might be tricyclic antidepressants in an elderly patient), we found that clinicians almost never stopped that medication once they had already previously prescribed it. On the other hand, the alert was effective at preventing new prescriptions for that medication in the elderly. Awdishu et al. (Awdishu 2016), looking at the impact of alerts on prescribing in patients with renal disease, also found that prospective alerts had a greater impact than look-back alerts (55.6% vs 10.3%).

Marcilly et al. developed evidence-based usability design principles for medication alerting systems (Marcilly 2018). They note that alerts should:

1. Improve the system’s signal-to-noise ratio
2. Support collaborative work, advocate a team approach and make the alert system a ‘team player’
3. Fit with clinicians’ workflow and their mental model
4. Display relevant data within the alert
5. Make the system transparent for the user
6. Include actionable tools within the alert

The Marcilly paper notes that alert design should take into account parameters such as the

patient’s clinical context or the clinician’s specialty. That makes sense. An alert to a primary care physician reminding them to adjust a medication dose based upon the patient’s renal function might just create unnecessary “noise” for a nephrologist entering a similar order. Similarly, regarding context, some alerts about renal dosing may not be appropriate for a patient already on dialysis.

Alerts are also more likely to be complied with if they offer “actionable” tools. For example, an alert that offers an alternative action or choice is much more likely to be complied with than one that simply suggests the original action is discouraged.

Shah et al. (Shah 2021) looked at CDS alerts regarding renal dosing in hospitalized patients. They found that alerts were nearly always presented inappropriately and were all overridden during the 1-year period studied. This was distinctly different from data they had previously seen in a legacy system in which medication-related CDS alerts associated with renal insufficiency had been found to be the most clinically beneficial. They identified several potential reasons why the current medication-related CDS alerts associated with renal insufficiency were less effective than they had been in the legacy homegrown system:

• No automatic calculation of level of renal function (CrCl or estimated GFR)
• No automatic dose adjustment
• No recommendations for alternatives
• No consideration of patient specific parameters, such as dialysis

The Shah study tells us we cannot simply adopt all vendor-generated CDS alerts and reminders. Rather, we must apply the same rigorous evaluation and monitoring to those alerts and reminders that we used when we designed all our own alerts and reminders. We need to make sure they are evidence-based, are actionable, offer alternatives where appropriate, are prospective, fit with workflow, take clinical context and clinician specialty into consideration, and, most of all, are limited in volume to those that are most likely to impact patient safety and patient outcomes so we can avoid alert fatigue.

We can’t duplicate the extensive literature review done by the ECRI Partnership. We encourage you to go back to their whitepaper (ECRI 2021). Their “evidence tables” in the appendix includes a summary of the findings from 12 key studies. We hope you’ll use lessons learned in those plus the key elements in today’s column to make sure you are getting the most out of your clinical decision support tools without generating alert fatigue and contributing to clinician burnout.

See some of our other Patient Safety Tip of the Week columns dealing with unintended consequences of technology and other healthcare IT issues:

• June 19, 2007 “Unintended Consequences of Technological Solutions”
• May 20, 2008 “CPOE Unintended Consequences – Are Wrong Patient Errors More Common?”
• June 17, 2008 “Technology Workarounds Defeat Safety Intent”
• August 26, 2008 “Pattern Recognition and CPOE”
• September 9, 2008 “Less is More….and Do You Really Need that Decimal?”
• December 16, 2008 “Joint Commission Sentinel Event Alert on Hazards of Healthcare IT”
• February 2009 “Healthcare IT The Good and The Bad”
• March 3, 2009 “Overriding Alerts…Like Surfin’ the Web”
• October 2009  “A Cautious View on CPOE”
• November 24, 2009 “Another Rough Month for Healthcare IT
  
• April 20, 2010 “HIT’s Limited Impact on Quality To Date”
• July 27, 2010 “EMR’s Still Have a Long Way to Go”
• March 22, 2011 “An EMR Feature Detrimental to Teamwork and Patient Safety”
• January 24, 2012 “Patient Safety in Ambulatory Care”
• June 26, 2012 “Using Patient Photos to Reduce CPOE Errors”
• June 2012 “Leapfrog CPOE Simulation: Improvement But Still Shortfalls”
• July 17, 2012 “More on Wrong-Patient CPOE”
• January 2013 “More IT Unintended Consequences”
• April 23, 2013 “Plethora of Medication Safety Studies”
• April 30, 2013 “Photographic Identification to Prevent Errors”
• October 8, 2013 “EMR Problems in the ED”
• March 11, 2014 “We Miss the Graphic Flowchart!”
• October 2014 “Ebola Exposes Fundamental Flaw”
• January 2015 “Beneficial Effect of EMR on Patient Safety”
• March 2015 “CPOE Fails to Catch Prescribing Errors”
• March 31, 2015 “Clinical Decision Support for Pneumonia”
• August 2015 “Newborn Name Confusion”
• December 2015 “Opioid Alert Fatigue”
• January 12, 2016 “New Resources on Improving Safety of Healthcare IT”
• January 19, 2016 “Patient Identification in the Spotlight”
• February 9, 2016 “It was just a matter of time…”
• April 5, 2016 “Workarounds Overriding Safety”
• May 2016 “Name Confusion in the Pharmacy”
• May 3, 2016 “Clinical Decision Support Malfunction”
• May 24, 2016 “Texting Orders – Is It Really Safe?”
• August 23, 2016 “ISMP Canada: Automation Bias and Automation Complacency”
• November 22, 2016 “Leapfrog, Picklists, and Healthcare IT Vulnerabilities”
• January 2017 “Joint Commission Thinks Twice About Texting Orders”
• February 28, 2017 “The Copy and Paste ETTO”
• March 2017 “Yes! Another Voice for Medication e-Discontinuation!”
• April 2017 “How Much Time Do We Actually Spend on the EMR?”
• June 27, 2017 “Texting – We Told You So!”
• August 1, 2017 “Progress on Wrong Patient Orders”
• January 2018 “Can We Improve Barcoding?”
• January 16, 2018 “Just the Fax, Ma’am”
• January 30, 2018 “Texting Errors Revealed”
• June 19, 2018 “More EHR-Related Problems”
• September 2018 “More Clinical Decision Support Successes”
• December 11, 2018 “Another NMBA Accident”
• January 1, 2019 “More on Automated Dispensing Cabinet (ADC) Safety”
• February 5, 2019 “Flaws in Our Medication Safety Technologies”
• March 26, 2019 “Patient Misidentification”
• May 2019 “Too Much Time on the EMR”
• May 21, 2019 “Mixed Message on Number of Open EMR Records”
• July 23, 2019 “Order Sets Can Nudge the Right Way or the Wrong Way”
• September 10, 2019 “Joint Commission Naming Standard Leaves a Gap”
• September 24, 2019 “EHR-related Malpractice Claims”
• December 17, 2019 “Tale of Two Tylers”
• June 2020 “EMR and Medication Safety: Better But Not Yet There”
• June 16, 2020 “Tracking Technologies”
• July 2020 “Patient Requests for EHR Corrections”
• July 21, 2020 “Is This Patient Allergic to Penicillin?”
• September 2020 “More on Workarounds”
• November 17, 2020 “A Picture Is Worth a Thousand Words”
• March 2021 “ECRI Partnership Whitepaper on Alert Fatigue”

See some of our previous columns dealing with the Leapfrog CPOE EHR evaluaton tool:

• July 27, 2010 “EMR’s Still Have a Long Way to Go”
• June 2012 “Leapfrog CPOE Simulation: Improvement But Still Shortfalls”
• April 23, 2013 “Plethora of Medication Safety Studies”
• March 2015 “CPOE Fails to Catch Prescribing Errors”
• May 3, 2016 “Clinical Decision Support Malfunction”
• November 22, 2016 “Leapfrog, Picklists, and Healthcare IT Vulnerabilities”
• June 2020 “EMR and Medication Safety: Better But Not Yet There”

References:

Cerqueira O, Gill M, Swar B, et al. The effectiveness of interruptive prescribing alerts in ambulatory CPOE to change prescriber behaviour & improve safety. BMJ Quality & Safety 2021; Published Online First: 19 April 2021

https://qualitysafety.bmj.com/content/early/2021/03/14/bmjqs-2020-012283

Shi Y, Amill-Rosario A, Rudin RS, et al. Barriers to using clinical decision support in ambulatory care: Do clinics in health systems fare better? Journal of the American Medical Informatics Association 2021; ocab064 Published: 25 April 2021

https://academic.oup.com/jamia/advance-article-abstract/doi/10.1093/jamia/ocab064/6250921?redirectedFrom=fulltext

Jankovic I., Chen JH. Clinical Decision Support and Implications for the Clinician Burnout Crisis. Yearbook of medical informatics 2020; 29(1): 145-154

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7442505/

Classen DC, Holmgren AJ, Co Z, et al. National Trends in the Safety Performance of Electronic Health Record Systems From 2009 to 2018. JAMA Netw Open 2020; 3(5): e205547

https://jamanetwork.com/journals/jamanetworkopen/fullarticle/2766545?resultClick=3

ECRI Partnership for Health IT Patient Safety. Safe Practices to Reduce CPOE Alert Fatigue through Monitoring, Analysis, and Optimization. ECRI 2021

https://d84vr99712pyz.cloudfront.net/p/pdf/hit-partnership/partnership_whitepaper_alertfatigue_final.pdf

Einbinder J, Hebel E, Wright A, Panzenhagen M, Middleton B. The number needed to remind: a measure for assessing CDS effectiveness. AMIA Annu Symp Proc 2014; 14: 506-515

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4419960/

Alagiakrishnan K, Ballermann M, Rolfson D, et al. Utilization of computerized clinical decision support for potentially inappropriate medications. Clin Interv Aging 2019; 14: 753–762

https://www.dovepress.com/utilization-of-computerized-clinical-decision-support-for-potentially--peer-reviewed-fulltext-article-CIA

Osheroff JA, Teich JM, Levick D, et al. Improving outcomes with clinical decision support: an implementer’s guide. 2nd ed. Chicago (IL): Healthcare Information and Management Systems Society; 2012

https://www.amazon.com/Improving-Outcomes-Clinical-Decision-Support/dp/0984457739/ref=sr_1_1?dchild=1&keywords=Osheroff&qid=1614095482&s=books&sr=1-1

Awdishu L, Coates CR, Lyddane A, et al. The impact of real-time alerting on appropriate prescribing in kidney disease: a cluster randomized controlled trial. J Am Med Inform Assoc 2016;  23(3): 609-616

https://academic.oup.com/jamia/article/23/3/609/2909002

Marcilly R, Ammenwerth E, Roehrer E, et al. Evidence-Based usability design principles for medication alerting systems. BMC Med Inform Decis Mak 2018; 18: 69

https://bmcmedinformdecismak.biomedcentral.com/articles/10.1186/s12911-018-0615-9

(Marcilly 2018)

Shah SN, Amato MG, Garlo KG, et al. Renal medication-related clinical decision support (CDS) alerts and overrides in the inpatient setting following implementation of a commercial electronic health record: implications for designing more effective alerts. Journal of the American Medical Informatics Association 2021; ocaa222

https://academic.oup.com/jamia/advance-article/doi/10.1093/jamia/ocaa222/6124727?searchresult=1#227144466

Print “How Are Alerts in Ambulatory CPOE Doing?”











To get "Patient Safety Tip of the Week "emailed to you, click here and enter "subscribe" in the subject field.



If you don't see the search term you expected to see here,  its probably because that tip already went to our Tip of the Week Archive. We do a new tip every week. Click here to search the entire site or you can Go to Tip of the Week Archive a patient safety resource solution loaded with tips, tools, and techniques you can use in your patient safety and quality improvement initiatives. Or it may have moved to our What's New Archive.

Click here to see the consulting services and patient safety solutions that we provide.

Click on the "Contact Us" button at the left to send us your comments on our "What's New in the Patient Safety World" columns.

To get "Patient Safety Tip of the Week "emailed to you, click here and enter "subscribe" in the subject field.



What's New in the Patient Safety World?

May 2021

·More on Time Spent on the EMR

·CLABSI’s Up in the COVID-19 Era

·Another Hands-Free Unintended Consequence

·Axe the Fax

More on Time Spent on the EMR

Clinicians spend an awful lot of time on the electronic medical record (EMR) and this has been an important factor contributing to burnout. See our What's New in the Patient Safety World columns for April 2017 “How Much Time Do We Actually Spend on the EMR?” and May 2019 “Too Much Time on the EMR”.

Many of the studies have looked at time spent on the EMR in the hospital setting. But a few have looked at EMR use in the ambulatory setting. A time-motion study of physicians in ambulatory practices (Sinsky 2016) found that, during the office day, physicians spent 27.0% of their total time on direct clinical face time with patients and 49.2% of their time on EHR and desk work. While in the examination room with patients, physicians spent 52.9% of the time on direct clinical face time and 37.0% on EHR and desk work. In addition, outside of office hours, physicians spend another 1 to 2 hours of personal time each night doing additional computer and other clerical work. Thus, for every hour physicians provide direct clinical face time to patients, they spent nearly 2 additional hours on EHR and desk work within the clinic day. Of the time spent on EHR and desk work, 38.5% was spent on documentation and review tasks, 6.3% on test results, 2.4% on medication orders, and 2.0% on other orders. They spent 1.1% of their time on administrative tasks (0.6% involved insurance-related tasks and 0.5% involved scheduling).

But it turns out that time spent on the EMR is far from uniform across ambulatory specialties. A new study looked at time spent on the EMR both during the day and after hours (Rotenstein 2021). Those researchers found that mean total active daily EMR time was 45.6 vs 85.7 vs. 115.0 minutes for surgical vs. medical vs. primary care specialties, respectively. Mean after hours active use time on the EMR was 16.0 vs 26.2 vs. 29.8 minutes, respectively.

The most time was spent on notes (22.0 minutes vs. 40.8 minutes vs. 51.5 minutes for surgical specialties, medical specialties, and primary care specialties, respectively). Clinical review and orders represented the next biggest areas of time expenditure. Time dealing with messages showed major differences. Compared with surgical colleagues, primary care clinicians received more than twice as many team-derived messages, 5 times as many patient messages, and 15 times as many prescription messages each day.

The authors call for further investigation to identify interventions to reduce the administrative and EMR burden to help avoid clinician burnout.

A second recent study (Eschenroeder 2021) confirmed the impact of after-hours EMR activity on burnout. The researchers found that physicians reporting ≤ 5 hours weekly of after-hours charting were twice as likely to report lower burnout scores compared to those charting ≥6 hours (aOR 2.43).

Of course, the EMR burden impact on burnout is not limited to physicians. Nurses are also impacted. A new study (Kutney-Lee 2021) found that nurses who worked in hospitals with poorer EHR (electronic health record) usability had significantly higher odds of burnout (odds ratio 1.41),  job dissatisfaction (OR 1.61) and intention to leave (OR 1.31) compared with nurses working in hospitals with better usability.

Not only did poor EHR usability impact nurse burnout, it also impacted patient safety and outcomes. Surgical patients treated in hospitals with poorer EHR usability had significantly higher odds of inpatient mortality (OR 1.21) and 30-day readmission (OR 1.06) compared with patients in hospitals with better usability.

See some of our other Patient Safety Tip of the Week columns dealing with unintended consequences of technology and other healthcare IT issues:

• June 19, 2007 “Unintended Consequences of Technological Solutions”
• May 20, 2008 “CPOE Unintended Consequences – Are Wrong Patient Errors More Common?”
• June 17, 2008 “Technology Workarounds Defeat Safety Intent”
• August 26, 2008 “Pattern Recognition and CPOE”
• September 9, 2008 “Less is More….and Do You Really Need that Decimal?”
• December 16, 2008 “Joint Commission Sentinel Event Alert on Hazards of Healthcare IT”
• February 2009 “Healthcare IT The Good and The Bad”
• March 3, 2009 “Overriding Alerts…Like Surfin’ the Web”
• October 2009  “A Cautious View on CPOE”
• November 24, 2009 “Another Rough Month for Healthcare IT
  
• April 20, 2010 “HIT’s Limited Impact on Quality To Date”
• July 27, 2010 “EMR’s Still Have a Long Way to Go”
• March 22, 2011 “An EMR Feature Detrimental to Teamwork and Patient Safety”
• January 24, 2012 “Patient Safety in Ambulatory Care”
• June 26, 2012 “Using Patient Photos to Reduce CPOE Errors”
• June 2012 “Leapfrog CPOE Simulation: Improvement But Still Shortfalls”
• July 17, 2012 “More on Wrong-Patient CPOE”
• January 2013 “More IT Unintended Consequences”
• April 23, 2013 “Plethora of Medication Safety Studies”
• April 30, 2013 “Photographic Identification to Prevent Errors”
• October 8, 2013 “EMR Problems in the ED”
• March 11, 2014 “We Miss the Graphic Flowchart!”
• October 2014 “Ebola Exposes Fundamental Flaw”
• January 2015 “Beneficial Effect of EMR on Patient Safety”
• March 2015 “CPOE Fails to Catch Prescribing Errors”
• March 31, 2015 “Clinical Decision Support for Pneumonia”
• August 2015 “Newborn Name Confusion”
• December 2015 “Opioid Alert Fatigue”
• January 12, 2016 “New Resources on Improving Safety of Healthcare IT”
• January 19, 2016 “Patient Identification in the Spotlight”
• February 9, 2016 “It was just a matter of time…”
• April 5, 2016 “Workarounds Overriding Safety”
• May 2016 “Name Confusion in the Pharmacy”
• May 3, 2016 “Clinical Decision Support Malfunction”
• May 24, 2016 “Texting Orders – Is It Really Safe?”
• August 23, 2016 “ISMP Canada: Automation Bias and Automation Complacency”
• November 22, 2016 “Leapfrog, Picklists, and Healthcare IT Vulnerabilities”
• January 2017 “Joint Commission Thinks Twice About Texting Orders”
• February 28, 2017 “The Copy and Paste ETTO”
• March 2017 “Yes! Another Voice for Medication e-Discontinuation!”
• April 2017 “How Much Time Do We Actually Spend on the EMR?”
• June 27, 2017 “Texting – We Told You So!”
• August 1, 2017 “Progress on Wrong Patient Orders”
• January 2018 “Can We Improve Barcoding?”
• January 16, 2018 “Just the Fax, Ma’am”
• January 30, 2018 “Texting Errors Revealed”
• June 19, 2018 “More EHR-Related Problems”
• September 2018 “More Clinical Decision Support Successes”
• December 11, 2018 “Another NMBA Accident”
• January 1, 2019 “More on Automated Dispensing Cabinet (ADC) Safety”
• February 5, 2019 “Flaws in Our Medication Safety Technologies”
• March 26, 2019 “Patient Misidentification”
• May 2019 “Too Much Time on the EMR”
• May 21, 2019 “Mixed Message on Number of Open EMR Records”
• July 23, 2019 “Order Sets Can Nudge the Right Way or the Wrong Way”
• September 10, 2019 “Joint Commission Naming Standard Leaves a Gap”
• September 24, 2019 “EHR-related Malpractice Claims”
• December 17, 2019 “Tale of Two Tylers”
• June 2020 “EMR and Medication Safety: Better But Not Yet There”
• June 16, 2020 “Tracking Technologies”
• July 2020 “Patient Requests for EHR Corrections”
• July 21, 2020 “Is This Patient Allergic to Penicillin?”
• September 2020 “More on Workarounds”
• November 17, 2020 “A Picture Is Worth a Thousand Words”
• March 2021 “ECRI Partnership Whitepaper on Alert Fatigue”

Some of our prior columns on “burnout”:

• August 2018               “Burnout and Medical Errors”
• October 16, 2018        “Burnout”
• February 9, 2021         “Nursing Burnout”

References:

Sinsky C, Colligan L, Li L, et al. Allocation of Physician Time in Ambulatory Practice: A Time and Motion Study in 4 Specialties. Ann Intern Med 2016; 165: 753-760

https://www.acpjournals.org/doi/10.7326/M16-0961

Rotenstein LS, Holmgren AJ, Downing NL, Bates DW. Differences in Total and After-hours Electronic Health Record Time Across Ambulatory Specialties. JAMA Intern Med 2021; Published online March 22, 2021

https://jamanetwork.com/journals/jamainternalmedicine/fullarticle/2777845

Kutney-Lee A, Brooks Carthon M, Sloane DM, Bowles KH, McHugh MD, Aiken LH. Electronic Health Record Usability: Associations With Nurse and Patient Outcomes in Hospitals. Med Care 2021; Apr 1, 2021

https://journals.lww.com/lww-medicalcare/Abstract/9000/Electronic_Health_Record_Usability__Associations.98172.aspx

Eschenroeder E, Manzione LC, Adler-Milstein J, et al. Associations of physician burnout with organizational electronic health record support and after-hours charting, Journal of the American Medical Informatics Association 2021; 28(5): 960-966

https://academic.oup.com/jamia/article/28/5/960/6242740

Print “May 2021 More on Time Spent on the EMR”

CLABSI’s Up in the COVID-19 Era

Several studies have found an increase in CLABSI’s (Central Line-Associated Bloodstream Infections) during the COVID-19 pandemic. Patel et al. (Patel 2021) used data reported to the Centers for Disease Control and Prevention’s National Healthcare Safety Network (NHSN) in almost 3000 acute care hospitals.  They compared standard infection ratios of CLABSI’s from April, May and June of 2019 to the same period of 2020. They found the rate of CLABSI’s increased from 0.68 in 2019 to 0.87 in 2020, an increase of 28%. Critical care units experienced the highest increase at 39% (from 0.75 to 1.04), followed by ward locations at 13%.

Fakih et al. (Fakih 2021) also used NHSN data to do a retrospective evaluation of CLABSI and CAUTI outcomes in 78 hospitals from a single healthcare system over 2 periods: before the COVID-19 pandemic (March 2019–February 2020; 12 months) and during the COVID-19 pandemic (March–August 2020; 6 months). CLABSI rates increased by 51.0% during the pandemic period from 0.56 to 0.85 per 1,000 line days and by 62.9% from 1.00 to 1.64 per 10,000 patient days. Hospitals with monthly COVID-19 patients representing >10% of admissions had a National Health Safety Network (NHSN) device standardized infection ratio for CLABSI that was 2.38 times higher than hospitals with <5% prevalence during the pandemic period. In contrast, no significant changes were identified for CAUTI’s (0.86 vs 0.77 per 1,000 catheter days).

A number of factors have been hypothesized as contributors to this increase in CLABSI rates. The frequency of contact with patients may have changed during the pandemic in attempt to reduce healthcare worker exposure to patients and to preserve personal protective equipment. Patients admitted during the pandemic were more likely to require critical care support and to need it for a longer period of time, potentially putting them at greater risk for CLABSI. The proportion of COVID-19 patients with CLABSI events was 5 times greater than for non–COVID-19 patients during the pandemic period. The average time from COVID-19 diagnosis to developing CLABSI was ∼18 days, indicating that the CLABSI events occurred in COVID-19 patients with prolonged hospitalization.

Qualitative feedback from their infection prevention teams reported changes to routine CLABSI prevention practices in ICUs, such as less universal decolonization (eg, mupirocin administration and chlorhexidine bathing), alterations in line care due to intravenous pumps placed in hallways (eg, extension tubing used and less bedside checks on lines), line and dressing integrity gaps related to prone positioning of patients, opportunities in scrub-the-hub compliance, and increases in line draws for blood cultures.

In addition, staffing changes responding to increased patient volume on the units, such as the help of traveling clinicians not as familiar with standard unit prevention practices, may have contributed.

They also noted that “line rounds”, which had been a routine practice prior to the COVID-19 pandemic, often stopped during the COVID-19 pandemic period due to competing priorities. Those rounds had helped ensure proper device selection, utilization, and bedside practices were being followed.

Line rounds are something we advocate be performed on a daily basis to reduce CLABSI’s (we also advocate “Foley rounds” daily to reduce CAUTI’s). During those rounds we consider the continued “appropriateness” of such devices.

The above studies do not separate CLABSI’s due to traditional central lines vs. peripherally inserted central lines (PICC’s). An important milestone in reducing CLABSI’s was publication of the Michigan Appropriateness Guide for Intravenous Catheters (MAGIC) (Chopra 2015), which provides evidence-based criteria for multiple types of vascular access devices but especially focused on peripherally inserted central catheter (PICC) use. Chopra and colleagues recently looked at whether implementing MAGIC reduces complications (Chopra 2021). They used data from 52 Michigan hospitals. During the preintervention period, the mean frequency of appropriate PICC use was 31.9% and the mean frequency of complications was 14.7%. Following the intervention, PICC appropriateness increased to 49.0% while complications decreased to 10.7%. Compared with patients with inappropriate PICC placement, appropriate PICC use was associated with a significantly lower odds of complications (OR 0.29), including a decrease in CLABSI’s (OR 0.61). There were also decreases in occlusion (OR 0.25) and VTE (OR 0.40).

Some of our other columns on IV access, central venous catheters and PICC lines:

January 21, 2014         “The PICC Myth”

December 2014           “Surprise Central Lines”

July 2015                    “Reducing Central Venous Catheter Use”

October 2015              “Michigan Appropriateness Guide for Intravenous Catheters”

March 27, 2018           “PICC Use Persists”

February 26, 2019       “Vascular Access Device Dislodgements”

July 16, 2019              “Avoiding PICC’s in CKD”

March 2, 2021             “Barriers to Timely Catheter Removal”

References:

Patel P, Weiner-Lastinger L, Dudeck M, et a;. Impact of COVID-19 Pandemic on Central Line-Associated Bloodstream Infections During the Early Months of 2020, National Healthcare Safety Network. Infection Control & Hospital Epidemiology 2021; 1-8 Published online by Cambridge University Press:  15 March 2021

https://www.cambridge.org/core/journals/infection-control-and-hospital-epidemiology/article/impact-of-covid19-pandemic-on-central-lineassociated-bloodstream-infections-during-the-early-months-of-2020-national-healthcare-safety-network/F4FBF17FE70FED931B54097A2AC400C9

Fakih MG, Bufalino A, Sturm L, et al. Coronavirus disease 2019 (COVID-19) pandemic, central-line-associated bloodstream infection (CLABSI), and catheter-associated urinary tract infection (CAUTI): The urgent need to refocus on hardwiring prevention efforts. Infect Control Hosp Epidemiol 2021; Published online 2021 Feb 19

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8007950/

Chopra V, Flanders SA, Saint S, et al. The Michigan Appropriateness Guide for Intravenous Catheters (MAGIC): Results from a Multispecialty Panel Using the RAND/UCLA Appropriateness Method. Ann Intern Med 2015; 163(6_Supplement): S1-S40

https://www.acpjournals.org/doi/10.7326/M15-0744?articleid=2436759&atab=7

Chopra V, O'Malley M, Horowitz J, et al. Improving peripherally inserted central catheter appropriateness and reducing device-related complications: a quasiexperimental study in 52 Michigan hospitals. BMJ Quality & Safety 2021; Published Online First: 29 March 2021

https://qualitysafety.bmj.com/content/early/2021/03/28/bmjqs-2021-013015

Print “May 2021 CLABSI’s Up in the COVID-19 Era”

Another Hands-Free Unintended Consequence

Some solutions sound intuitive. But common sense doesn’t always pan out. When it comes to hand hygiene, it is logical that transmission of infectious agents should be reduced if you don’t have to touch various surfaces. But, is that borne out in practice?

Electronic faucets are one such example. The idea is great. You don’t have to touch the faucet to turn it on. It simply turns on when it senses the presence of your hands beneath the faucet. In our May 2011 What's New in the Patient Safety World column “The Best Laid Plans,,,Electronic Water Faucet Paradox” we noted that researchers at Johns Hopkins demonstrated 50% of electronic water faucets grew Legionella species, compared to 15% of manual faucets. They felt that the complex valve structure of the electronic faucets predisposed to growth of Legionella. While some wanted more studies to confirm this finding, Hopkins was so concerned that they removed 20 electronic faucets in patient care areas and cancelled planned installation of about 1000 such faucets in a new clinical building.

Now a new study questions use of high speed air dryers (Moura 2021). These are devices that blow warm or hot air over your hands to dry them off after you wash them. Theoretically, if you don’t have to touch the device, you would be less likely to get contamination compared to touching a paper towel dispenser. Moura et al. used a bacteriophage as a surrogate for bacterial pathogens and compared bacteriophage counts on volunteers’ hands dried via high speed air dryers vs. those dried by paper towels. The volunteers first cleansed their hands or gloved hands in 70% alcohol gel, then immersed their hands in the study solution containing the bacteriophage. The researchers then measured bacteriophage levels not only on the volunteers’ hands, but also on their clothing and on surfaces they might touch (eg. stethoscope, arms of a chair, and several other surfaces).

Both the jet air dryer and the paper towel methods significantly reduced bacteriophage contamination of the hands. But, apron (simulated trunk or clothing) contamination by bacteriophage during hand drying was significantly higher after jet air dryer use. The bacteriophage levels detected on the volunteers’ hands at the end of the experiments suggested gross persistence of bacteriophage contamination throughout the sampling period.

Moreover, all 8 surfaces investigated following jet air dryer use had bacteriophage contamination above the limit of detection, whereas this occurred for only 5 surfaces after paper towel use. For all samples, there was a significantly higher level of surface contamination following hand drying with the jet air dryer than with paper towels. Samples obtained from smaller surface areas, namely elevator and ward access buttons, showed lower bacteriophage contamination. Interestingly, simulated use of a hospital phone for 10 seconds resulted in detectable contamination only following jet air dryer use. The average surface contamination following hand contact was >10-fold higher after jet air dryer use than after paper towel use (4.1 log10 copies/µL versus 2.9 log10 copies/µL, respectively).

This, of course, is not the first study to warn of potential contamination from high speed air dryers. Best et al. (Best 2018) compared bacterial contamination levels in washrooms with hand-drying by either paper towels (PT) or jet air dryer (JAD). Bacterial contamination was lower in PT versus JAD washrooms. Total bacterial recovery was significantly greater from JAD versus PT dispenser surfaces and significantly more bacteria were recovered from JAD washroom floors. Multiple examples of significant differences in surface bacterial contamination, including by fecal and antibiotic-resistant bacteria, were observed, with higher levels in JAD versus PT washrooms. The authors concluded that hand-drying method affects the risk of (airborne) dissemination of bacteria in real-world settings.

The findings of these studies certainly question the use of hand drying with jet air dryers in a hospital setting.

References:

Moura I, Ewin D, Wilcox M. From the hospital toilet to the ward: A pilot study on microbe dispersal to multiple hospital surfaces following hand drying using a jet air dryer versus paper towels. Infection Control & Hospital Epidemiology 2021; 1-4

Published online 17 March 2021

https://www.cambridge.org/core/journals/infection-control-and-hospital-epidemiology/article/from-the-hospital-toilet-to-the-ward-a-pilot-study-on-microbe-dispersal-to-multiple-hospital-surfaces-following-hand-drying-using-a-jet-air-dryer-versus-paper-towels/FA51D26C9C3DC261D35F122EF97593D5

Best E, Parnell P, Couturier J, et al. Environmental contamination by bacteria in hospital washrooms according to hand-drying method: a multicentre study. J Hosp Infect 2018; 100: 469-475

https://www.sciencedirect.com/science/article/pii/S0195670118303669

Print “May 2021 Another Hands-Free Unintended Consequence”

Axe the Fax

We’ve done multiple columns on problems created by use of fax in healthcare. But, it just won’t go away! A recent opinion column in the Toronto Star (Singh 2021) serves as a reminder that fax machine use in healthcare just won’t die!

The problem really is one of interoperability, or rather, lack of interoperability. Singh notes that millions of medical records are faxed in Ontario every month. He points out that doctors’ offices and hospitals use various electronic medical record systems to document patients’ medical information, but if they want to send a patient to a specialist or a prescription to a pharmacy, they often need to print out the paperwork and fax it.

He compares that to the equivalent of drafting an email, printing it out, and then mailing it to the recipient.

Moreover, Singh notes that about 20% of faxes sent on traditional fax machines fail daily. That leads to many hours of unnecessary work and inefficiency. That leads to errors, lost patient information, and slows down the process of getting patients connected to the health care they need.

Beth Gerritsen, who did a Masters thesis on fax usage in Ontario, notes that the COVID-19 pandemic has exacerbated problems related to use of fax in healthcare (Gerritsen 2021). She notes that, before the pandemic, the healthcare system’s reliance on the fax was embarrassing, but now it’s a critical failure point for the entire system. Her work on fax usage in Ontario showed that:

• 35% to 40% of primary care administrative time is fax-related
• Every month, approximately two million e-faxes are sent from our EMRs 
• Regional home care service requests and coordination occur mostly by fax, estimated at 1.7 million a year
• Ontario’s Cancer Screening programs depend highly on fax, with over 750,000 faxed orders for Colon Cancer Screening Kits sent between July 2019 to July 2020
• Roughly 10% of fax referrals go to the wrong place causing risks with a delay in care
• 63% of all unauthorized disclosures of personal health information is due to misdirected fax
• Roughly 10% of fax referrals go to the wrong place causing risks with a delay in care
• Approximate 20% faxes fail when sent from a traditional fax machine on any given day

Gerritsen notes that, during the pandemic, clinicians stepped up with a quick shift to virtual care in order to support patients but quality virtual care needs proper support from digital infrastructure. She notes that a fax failure of a prescription or lab order after a virtual visit critically impacts a patient and nobody should experience a delay in a referral for specialty care because of a misdirected or a failed fax transmission.

She goes on to discuss the steps Ontario needs to take to move away from use of fax in healthcare. 

Though both Singh and Gerritsen are discussing use of fax in Ontario, the situation in the US is not much better. Yes, we are making strides in improving interoperability but every hospital and physician’s office in the US still relies on fax at least to some degree. Our January 16, 2018 Patient Safety Tip of the Week “Just the Fax, Ma’am” discussed a podcast on faxing in US doctors’ offices by Sarah Kliff and colleagues on Vox’s “The Impact” series (Kliff 2017). And, even where hospitals and physician’s offices have joined in regional healthcare information exchanges, other third parties that must receive healthcare information (eg. insurers, home care agencies, etc.) may not be included.

Our Patient Safety Tips of the Week for June 19, 2012 “More Problems with Faxed Orders” and January 16, 2018 “Just the Fax, Ma’am” outline many patient safety issues associated with use of faxes.

It’s worth repeating some of the caveats we raised in our June 19, 2012 Patient Safety Tip of the Week “More Problems with Faxed Orders” and other columns. The problem we have mentioned most often is the missed decimal point (where lines or smudge during fax transmission and printing obscures a decimal point) and the patient receives a 10x overdose of the medication. (In our September 9, 2008 Patient Safety Tip of the Week “Less is More….and Do You Really Need that Decimal?” we cautioned against even using a decimal point when the fraction following the decimal point is clinically irrelevant because that decimal point may be overlooked, especially in faxed orders.) The opposite, of course, may also occur where a smudge on the fax looks like a decimal point (the phantom decimal point) so the patient receives one-tenth the intended amount.

But we’ve also mentioned the case where 2 sheets put into a fax machine stick together and thus only one sheet gets transmitted (see our January 18, 2011 Patient Safety Tip of the Week “More on Medication Errors in Long-Term Care” where we cited such an example from ISMP 2010). Unless you have a cover fax sheet that says “3 pages (cover sheet plus 2 others)” the receiving party may not realize that they are missing a page.

We’ve also seen cases where faxes on multiple patients are sent out at the same time and the receiving party does not recognize that the second sheet is actually for a different patient (see our January 18, 2011 Patient Safety Tip of the Week “More on Medication Errors in Long-Term Care”).

Just as with handwritten orders, on a faxed order with a drug ending in the letter “L” if there is insufficient space between the “L” and the next number, the receiver may think the “L” is actually a “1” (one) and give a dose 10 times too high. And dangerous abbreviations may show up even more frequently on faxed orders than orders written on-site because the provider is more likely to have access to the “do not use” abbreviation list when on-site.

Another mistake is when a person faxes documents that have information on both sides and does not realize that only one side of each page is being faxed.

And remember when you are sending a fax that some elements (eg. text in a different color) may fail to be seen when transmitted. Or that highlighted items (eg. items you tied to stress with a yellow highlighter) may appear blacked out on the received fax! (Reminds me of the time in college when I asked a friend to send me his notes from a class I had missed so I could study for a test the next day. He faxed them and all the important stuff, which he had highlighted with a highlighting marker, was blacked out on the fax!!!).

And one of the most egregious errors of all – faxing to the wrong phone number (the misdirected fax). Ever get a call from the local supermarket that you faxed them a sheet with PHI on it? Your HIPAA compliance officer and risk manager will turn gray when that call comes in! We’ve seen faxes sent to old fax numbers after a physician has moved to a new office and even faxes sent to physicians who have been deceased for four years! And hospital computer systems often have the wrong physician listed as primary care physician, often leading to faxes being sent to the wrong PCP.

ISMP Canada (ISMP Canada 2012) came up with a new fax error – the truncation error. They provide a great example of a faxed order for “dalteparin” where the “da” gets cut off in the fax and the “lt” looks like an “H” on the fax, resulting in what clearly looks like an order for “Heparin”. Click on the link above and you’ll see both the faxed prescription and the original.

Note that prescription has lots of other bad errors on it. It uses the do-not-use abbreviation “U” (for units) as well as 2 other abbreviations that should be avoided (“SQ” for subcutaneous and “QD” for once daily). It has a different dose written above and crossed out. And it does not have listed the indication for the drug. It also has an illegible word following the “QD” (is it nitely? or is it a provider’s signature?). And there is nothing on the prescription to indicate the duration of therapy, amount to be dispensed, whether it should be refilled, etc. Who would have thought one prescription could be used as a primer for medication errors!

ISMP Canada notes the importance of reviewing copies of the fax you send or the one you receive. For instance, in the case given one might have noticed that the name of the hospital was also truncated, which might have been a clue that the medication name was truncated. They also note in the example given that the dosing frequency would have been unusual for heparin (it is usually given twice daily or three times daily rather than once daily), perhaps being another clue to the receiver that there was an error. They also note that including both the generic and brand names on the prescription would have provided another clue to the error. They note the importance of engaging the patient to be on the lookout for errors as well.

We refer you back to our Patient Safety Tips of the Week for June 19, 2012 “More Problems with Faxed Orders” and January 16, 2018 “Just the Fax, Ma’am” for our multiple recommendations on faxing issues.

Our January 2019 What's New in the Patient Safety World column “Still Faxing?” noted initiatives in the UK and the US to eliminate use of fax in healthcare. But we are still not there. Both Singh and Gerritsen use the catchy phrase “Axe the Fax”. It seems that, in politics, catchy 3-word phrases go a long way. Maybe it’s time we all adopt “Axe the Fax”!

See our prior columns on problems related to use of fax in healthcare:

June 19, 2012              “More Problems with Faxed Orders”

January 16, 2018         “Just the Fax, Ma’am”

September 2018          “ECRI Institute Partnership: Closing the Loop”

January 2019               “Still Faxing?”

References:

Singh P, Aggarwal S. We need to axe the fax in health care — now. Toronto Star 2021; March 24, 2021

https://www.thestar.com/opinion/contributors/2021/03/24/we-need-to-axe-the-fax-in-health-care-now.html

Gerritsen B. Axe the fax: A primer on fax tech in the 21st century, an Ontario’s healthcare system perspective. Canadian Healthcare Network. The Medical Post 2021

https://www.canadianhealthcarenetwork.ca/axe-the-fax-a-primer-on-fax-tech-in-the-21st-century-an-ontarios-healthcare-system-perspective

Kliff S, Pinkerton B, Weinberger J, Drozdowska A. It’s 2017. Why does medicine still run on fax machines? Vox “The Impact” (podcast) 2017; October 30, 2017

https://www.vox.com/2017/10/30/16387306/american-medicine-healthcare-fax-machine

ISMP (Institute for Safe Medication Practices). Order scanning systems (and fax machines) may pull multiple pages through the scanner at the same time, leading to drug omissions. ISMP Medication Safety Alert (Nurse Advise-ERR) 2010; 8(11):  1-2

http://www.ismp.org/newsletters/nursing/default.asp

ISMP Canada.  ALERT: Medication Mix-up with a Faxed Prescription. ISMP Canada Safety Bulletin 2012; 12(6): 1-3 June 5, 2012

http://www.ismp-canada.org/download/safetyBulletins/2012/ISMPCSB2012-06_Alert-MedMixupwithFaxedPrescription.pdf

Print “May 2021 Axe the Fax”

Print “May 2021 What's New in the Patient Safety World (full column)”

Print “May 2021 More on Time Spent on the EMR”

Print “May 2021 CLABSI’s Up in the COVID-19 Era”

Print “May 2021 Another Hands-Free Unintended Consequence”

Print “May 2021 Axe the Fax”



Go to the "Whats New Archive"

To get "What's New in the Patient Safety World"emailed to you,click here and enter "subscribe" in the subject field.

To get "What's New in the Patient Safety World"emailed to you,click here and enter "subscribe" in the subject field.