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One of the biggest gaps in medication safety is failed discontinuation of medications. A clinician decides to discontinue the medication and either enters an order for that discontinuation or simply tells the patient to stop taking the medication. But the community pharmacy or mail order pharmacy is never notified of that discontinuation and continues to dispense that medication. Our multiple prior columns on this problem are listed below.
Enter a tool called CancelRx. We mentioned CancelRx in our March 2017 What's New in the Patient Safety World column “Yes! Another Voice for Medication e-Discontinuation!”. Researchers at the University of Wisconsin recently demonstrated the value of CancelRx in reducing outpatient medication discrepancies by ensuring communication of medication discontinuation to pharmacies (Watterson 2021).
CancelRx integrates with clinic EHR and pharmacy dispensing software and automates the manual process that was previously delegated to clinic and pharmacy staff. It automatically sends an electronic notification of a medication discontinuation from a clinic’s EHR to a pharmacy’s dispensing software. After a clinic prescriber has discontinued a medication and indicated that the pharmacy should be notified, the order is processed by a third-party vendor, in this case SureScripts (the same platform used to communicate electronic prescriptions). For the cancellation message to be electronically transmitted via CancelRx, the functionality must be “turned on” at SureScripts for both the clinic sending the message and the pharmacy receiving the message.
The research team used an interrupted time series analysis (ITSA) to evaluate the effect of CancelRx to decrease medication discrepancies in the EHR and pharmacy management software. The impact was quite striking. Approximately 34% of prescriptions were successfully cancelled in the pre-CancelRx period. There was an immediate and significant increase in the proportion of successful medication discontinuations after CancelRx implementation, with an average of 92.78% prescriptions successfully discontinued in the post period. The impact was sustained in the year after the initial launch.
Of interest was a disparity between primary care and specialty care clinics. The ITSA found that there were significant differences between the proportion of successful medication discontinuations pre-CancelRx implementation (difference 17.7%, P<0.001). Specialty clinics had a greater proportion of medications that were successfully cancelled in the preintervention period compared to primary care clinics. During the year prior to CancelRx implementation, the percentage of medications successfully cancelled from primary care clinics was approximately 26%, whereas the percentage from specialty clinics was approximately 44%. However, immediately after CancelRx implementation, the proportion of successful cancellations across the 2 clinic types converged and became the same on average (approximately 98% in both the primary care and specialty clinics, difference 1.6%).
Also, prior to CancelRx implementation there was considerable variation in the time to medication discontinuation. In comparison, after CancelRx implementation, medication discontinuations were all completed on the same day!
CancelRx requires that both the clinic and the pharmacy have the functionality turned on through the third-party vendor.
Watterson et al. note that CMS added CancelRx to the 2017 Stage 3 Meaningful Use EHR Certification Criteria, required to qualify for the Medicaid Promoting Interoperability Program. Certification criteria requires that a user be able to not only create, change, or refill but also cancel prescriptions within the EHR technology according to NCPDP SCRIPT Standard (which includes CancelRx). But, for a variety of reasons, organizations have been slow to adopt this functionality. The authors note, however, that more and more entire health systems, private clinics, and pharmacies are now upgrading their systems to receive and utilize CancelRx functionality.
The results of the Watterson study should serve as an impetus for all health systems and clinics to begin using CancelRx.
Some of our other columns on failed discontinuation of medications:
May 27, 2014 “A Gap in ePrescribing: Stopping Medications”
March 2017 “Yes! Another Voice for Medication e-Discontinuation!”
February 2018 “10 Years on the Wrong Medication”
August 28, 2018 “Thought You Discontinued That Medication? Think Again”
December 18, 2018 “Great Recommendations for e-Prescribing”
August 2019 “Including Indications for Medications: We Are Failing”
August 6, 2019 “Repeat Adverse Drug Events”
Watterson TL, Stone JA, Brown R, et al. CancelRx: a health IT tool to reduce medication discrepancies in the outpatient setting, Journal of the American Medical Informatics Association 2021; 28(7): 1526-1533
Back in the early 2000’s we had a regional collaborative on CKD (chronic kidney disease) in Western New York that involved all the hospitals, payers, nephrologists and primary care physicians. Our goal was to increase the early referral of patients with advanced CKD to nephrologists. That goal was based on data that showed those patients referred to nephrologists more than a year prior to dialysis had reduced mortality in the first year of dialysis. Patients referred late often had their first dialysis done under emergent conditions and tended not to fare as well as those who had plans for dialysis in advance of the actual need for dialysis. Potential benefits of earlier referral would include not only reduced mortality but also reduced hospital stays, fewer catheter-related complications, and lower costs.
We were very pleased that a major offshoot of our collaborative was adoption of reporting the eGFR by the major national commercial labs in addition to our local hospital labs.
At the time, we recognized that there were far too few nephrologists both locally and nationally to handle all the potential patients that would be identified as having late stage CKD. So, a big part of our collaborative was to provide primary care physicians with the tools to manage early CKD better. In addition to early referral of those patients with later stage CKD, a major focus was on factors that could reduce progression of early CKD to later stages.
But doing the logical thing does not always result in the desired outcome and it can sometimes have unintended consequences. In our February 2009 What's New in the Patient Safety World column “Unintended Consequences of eGFR Reporting” we discussed a study (den Hartog 2009) raising concerns about automatic eGFR reporting. That study confirmed the positive outcomes of using eGFR (identifying CKD earlier, preventing some deaths and progression to ESRD. However, it also notes the potential impact of false negative test results (identifying some incorrectly as having CKD). Those patients often undergo further testing that may not have been necessary.
A couple recent studies have also suggested we are probably overdiagnosing CKD. Duggal et al. (Duggal 2021) did a retrospective analysis of almost 400,000 veterans with CKD and looked at laboratory referral criteria based on VA/Department of Defense guidelines, predicted risk for kidney failure using the Kidney Failure Risk Equation (which incorporates age, eGFR, gender, and urine albumin-to-creatinine ratio), and the combination of laboratory referral criteria and predicted risk.
Slightly more than 66,000 patients met laboratory indications for referral and 17.7% of these were referred to nephrology in the following year. But the median two-year predicted risk of kidney failure was 1.5% among all patients meeting laboratory referral criteria. If referral were restricted to patients with predicted risk ≥1% in addition to laboratory indications, the potential referral volume would be reduced from 66,276 to 38,229 patients. If referrals were based on predicted risk alone, a two-year risk threshold of 1% or higher would identify a similar number of patients (N=72,948) as laboratory-based criteria with median predicted risk of 2.3%.
Note that NICE (National Institute for Health and Care Excellence) recently updated its guideline for chronic kidney disease assessment and management (NICE 2021) and recommends referral of adults with CKD for specialist assessment if they have a five year risk of needing renal replacement therapy of >5% (measured with the Kidney Failure Risk Equation).
Liu et al. (Liu 2021) noted that using the same level of estimated glomerular filtration rate (eGFR) to define chronic kidney disease (CKD) regardless of patient age may classify many elderly people with a normal physiological age-related eGFR decline as having a disease. So, they constructed an age-adapted model, comparing a fixed eGFR threshold of 60 vs thresholds of 75, 60, and 45 mL/min/1.73 m2 for age younger than 40, 40 to 64, and 65 years or older, respectively.
With this age-adapted approach, the size of the affected population shrank by more than one-third (from127,132 to 81,209 cohort members) compared with the standard approach based on a fixed eGFR cut point of 60 mL/min/1.73m2. That reduction was largely driven by a reclassification of older adults with isolated mild to moderate reductions in eGFR. Of those individuals 65 years or older in the fixed-threshold cohort who had baseline eGFR of 45 to 59 mL/min/1.73 m2 with normal/mild albuminuria, the 5-year risks of kidney failure and death were similar to those of non-CKD controls. The authors conclude that the current criteria for CKD that use the same eGFR threshold for all ages may result in overestimation of the CKD burden in an aging population, overdiagnosis, and unnecessary interventions in many elderly people who have age-related loss of eGFR.
In an editorial accompanying the Liu study, O’Hare et al. (O'Hare 2021) note that guidelines for the management of CKD developed in 2002 and updated in 2012 did not differentiate risk based on patient age. They also noted that, though the entities producing those guidelines were not-for-profits, they did have significant sponsorship by industry. They note that the Liu article highlights an important truth: how diseases are defined can have major implications for who meets the case definition, what treatments are and are not recommended, and the size and characteristics of the population affected. They note that “labeling many adults with isolated mild to moderate reductions in eGFR with a diagnosis of CKD exposes them to the potential harms of unnecessary medical tests, procedures, and treatments and possible psychological distress while offering little or nothing in return.”
The updated NICE guideline also recommended discontinuing adjustment for ethnicity when calculating estimated glomerular filtration rate (eGFR) in people from black ethnic groups. The UK Kidney Association and partner organizations have supported that change on the grounds that it further exacerbates health inequalities by overestimating kidney function in these groups.
A joint task force of the National Kidney Foundation and American Society of Nephrology has also just recommended a new Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) creatinine equation, which excludes the race variable (Delgado 2021).
Two studies published in the New England Journal of Medicine in September analyzed multiple eGFR equations and concluded that the race variable should be excluded from equations estimating GFR. Inker et al. (Inker 2021) found that new eGFR equations that incorporate creatinine and cystatin C but omit race are more accurate and led to smaller differences between Black participants and non-Black participants than new equations without race with either creatinine or cystatin C alone. Hsu et al. (Hsu 2021) also analyzed various methods of estimating renal function using equations. They found that using serum cystatin C instead of serum creatinine would yield equivalent GFR estimation without the need to consider race or ancestry. They do note that challenges regarding the cost, calibration, and standardization of cystatin C measurements would have to be addressed, but they anticipate that cost reduction could occur with broad adoption over time.
The editorial accompanying those 2 studies (Williams 2021) points out that all equations that estimate GFR are imperfect but that meaningful ways to alleviate health care inequities are overdue and the new recommendations do so without compromising the utility of these estimates. Williams et al. noted that these promising options will take time to implement, since measurement of cystatin C is currently neither routine nor uniform.
The Duggal and Liu studies provide a stark reminder that our best intentions often result in actions that have unintended consequences. We are in much better position today to tailor the guidelines to focus on those individuals who are most likely to have progression of decline in renal function that is likely to become significant in their lifetime. Focusing on those patients should lead to more rational use of resources and avoid unnecessary testing and interventions in those not likely to have progression.
Some of our prior columns on dialysis, CKD, and ESRD:
March 26, 2007 “Alarms Should Point to the Problem”
February 2009 “Unintended Consequences of eGFR Reporting”
September 20, 2011 “When Practice Changes the Evidence: The CKD Story”
September 2013 “Is Nephrologist Caseload Related to Dialysis Mortality?”
September 2014 “New Tubing Connections”
June 23, 2015 “Again! Mistaking Antiseptic Solution for Radiographic Contrast”
November 1, 2016 “CMS Emergency Preparedness Rule”
April 25, 2017 “Dialysis and Alarm Fatigue”
July 16, 2019 “Avoiding PICC’s in CKD”
December 10, 2019 “Dialysis Line Dislodgements”
February 4, 2020 “Drugs and Chronic Kidney Disease”
den Hartog JR, Reese PP, Cizman B, Feldman HI. The costs and benefits of automatic estimated glomerular filtration rate reporting. Clinical Journal of the American Society of Nephrology (CJASN) 2009 4(2): 419-427 February 1, 2009
Duggal V, Montez-Rath ME, Thomas I-C, et al. Nephrology Referral Based on Laboratory Values, Kidney Failure Risk, or Both: A Study Using Veterans Affairs Health System Data. Am J Kidney Diseases 2021; Published online: August 24, 2021
The Kidney Failure Risk Equation (KFRE)
NICE (National Institute for Health and Care Excellence). Chronic kidney disease: assessment and management. NICE guideline [NG203] Published: 25 August 2021
Liu P, Quinn RR, Lam NN, et al. Accounting for Age in the Definition of Chronic Kidney Disease. JAMA Intern Med 2021; Published online August 30, 2021
O’Hare AM, Rodriguez RA, Rule AD. Overdiagnosis of Chronic Kidney Disease in Older Adults—An Inconvenient Truth. JAMA Intern Med 2021; Published online August 30, 2021
Delgado C, Baweja M, Crews DC, et al. A Unifying Approach for GFR Estimation: Recommendations of the NKF-ASN Task Force on Reassessing the Inclusion of Race in Diagnosing Kidney Disease. American Journal of Kidney Diseases 2021; Published online September 23, 2021
Inker LA, Eneanya ND, Coresh J, et al. New Creatinine- and Cystatin C–Based Equations to Estimate GFR without Race. NEJM 2021; September 23, 2021
Hsu C, Yang W, Parikh RV, at al. Race, Genetic Ancestry, and Estimating Kidney Function in CKD. NEJM 2021; September 23, 2021
Williams WW, Hogan JW, Ingelfinger JR. Time to Eliminate Health Care Disparities in the Estimation of Kidney Function. NEJM 2021; September 23, 2021
The COVID-19 pandemic appears to have reversed the previous trend toward decreases in HAI’s (hospital-associated infections). Researchers used data from the National Healthcare Safety Network (NHSN), the nation’s largest HAI surveillance system, to analyzed recent trends in HAI’s (Weiner-Lastinger 2021). Early in 2020 there was a slight decrease in HAI’s compared to the same period in 2019. Then the pandemic hit. The remainder of 2020 saw significant national increases in CLABSI’s (central line–associated bloodstream infections), CAUTI’s (catheter-associated urinary tract infections), VAE’s (ventilator-associated events), and MRSA infections compared to 2019.
CLABSI’s, which had actually decreased 12% in the first quarter of 2020, increased 46% to 47% in the third quarter and fourth quarters of 2020 compared to 2019.
CAUTI’s increased significantly with the fourth quarter increasing by 19% compared to 2019.
VAE’s had significant increases nationally in all 4 quarters of 2020 compared to 2019, with the largest increase of 45% occurring in Q4.
MRSA bacteremia saw increases of 23% and 34% during 2020-Q3 and 2020-Q4 compared to 2019.
Decreases in SSI’s (surgical site infections) in 2020 likely reflected a substantial decrease in the number of adult inpatient colon or abdominal hysterectomy procedures (the 2 types of surgery included in the data) done during the pandemic.
Interestingly, C difficile–associated infections (CDI) decreased throughout 2020 compared to 2019. The authors attributed the decrease in CDI to increased focus on hand hygiene, environmental cleaning, patient isolation, and use of PPE during 2020, combined with continued inpatient antimicrobial stewardship programs and a marked decline in outpatient antibiotic prescribing,
It really should come as no surprise that HAI’s would increase during the pandemic. The increase in COVID-19 hospitalizations have put an incredible strain on hospital resources. Many more patients required intensive care, with increased use of ventilators. The authors also note that a longer patient length-of-stay, additional comorbidities and higher patient acuity levels, and a longer duration of device use in 2020 could have contributed to an overall increased risk of a device-associated infection during the pandemic. They also note that some studies identified an increased risk of ventilator associated conditions in critically ill COVID-19 patients
One would also suspect that PPE shortages, staffing shortages, burnout, and increased patient burden were likely factors contributing to the increase in most of these HAI’s.
The resurgence of COVID-19 infections and hospitalizations in 2021, driven by emergence of the delta variant, forbodes continued high levels of HAI’s.
Some of our prior columns on HAI’s (hospital-acquired infections):
December 28, 2010 “HAI’s: Looking In All The Wrong Places”
October 2013 “HAI’s: Costs, WHO Hand Hygiene, etc.”
February 2015 “17% Fewer HAC’s: Progress or Propaganda?”
April 2016 “HAI’s: Gaming the System?”
September 2016 “More on Preventing HAI’s”
November 2018 “Privacy Curtains Shared Rooms and HAI’s”
December 2018 “HAI Rates Drop”
January 2019 “Oral Decontamination Strategy Fails”
February 2019 “Infection Prevention for Anesthesiologists”
March 2019 “Does Surgical Gowning Technique Matter?”
May 2019 “Focus on Prophylactic Antibiotic Duration”
July 2019 “HAI’s and Nurse Staffing”
February 2020 “NICU: Decolonize the Parents”
June 16, 2020 “Tracking Technologies”
August 2020 “Surgical Site Infections and Laparoscopy”
December 2020 “Do You Have These Infection Control Vulnerabilities?”
May 2021 “CLABSI’s Up in the COVID-19 Era”
August 2021 “Updated Guidelines on C. diff”
Weiner-Lastinger L, Pattabiraman V, Konnor R, et al. The impact of coronavirus disease 2019 (COVID-19) on healthcare-associated infections in 2020: A summary of data reported to the National Healthcare Safety Network. Infection Control & Hospital Epidemiology 2021; 1-14 Published online 03 September 2021
Our July 20, 2021 Patient Safety Tip of the Week “FDA Warning: Magnets in Consumer Electronics May Affect Medical Devices” warned of the risk to cardiac devices, such as pacemakers and implanted cardioverter-defibrillators (ICD’s), by magnets in some consumer electronics, like cell phones and smartwatches. A few reports of such products leading to deactivation of the cardiac devices led to a warning from the FDA (FDA 2021a).
A new study (Seidman 2021) analyzed the separation distance between consumer electronic devices that may create magnetic interference, including cell phones and smart watches, and implantable pacemakers and ICD’s where “magnet mode” can be triggered. Many medical devices are designed with a “magnet mode” to allow for safe operation during certain medical procedures, such as undergoing an MRI scan. These safety features are typically initiated with the use of a high field strength magnet that is placed near the implanted device placing it into a “magnet mode.”
The researchers measured static magnetic fields of the iPhone 12 models and Apple Watch at several planes in 1 cm resolution. They found that all iPhone 12 and Apple Watch 6 models tested have static magnetic fields significantly greater than 10 gauss in close proximity (1–11 mm), which attenuates to below 10 gauss between 11 and 20 mm. Translation: If placed within close proximity, those magnetic fields are high enough to place implanted cardiac devices into magnet mode. When a separation distance of 6 inches is maintained between an iPhone 12 (or Apple Watch 6), the implantable device should not be put into magnet mode.
Those findings lend credence to the recommendations in the FDA warning. The FDA provided information for patients on this issue (FDA 2021b), stating “People with implanted medical devices may want to take some simple precautions, including:
While the overall risk of a smartphone or smartwatch deactivating your cardiac device may be low, the increasing use of strong magnets in the smartphones and smartwatches certainly raises concerns. It would be pretty easy to put such a cell phone in a pocket overlying a device or inadvertently place their smartwatch in close proximity to their cardiac device and be unaware that their cardiac device is in a mode that will not save them if they have an event.
The smartphones and smartwatches are being touted for their health safety capabilities. But patients should also be made aware of this potentially detrimental threat as well.
FDA (US Food and Drug Administration). FDA In Brief: FDA Continues to Monitor the Effects of Magnets in Consumer Electronics on Implanted Medical Devices. FDA 2021; May 13, 2021
Seidman SJ, Guag J, Beard B, Arp Z. Static magnetic field measurements of smart phones and watches and applicability to triggering magnet modes in implantable pacemakers and implantable cardioverter-defibrillators. Heart Rhythm 2021; Published online: August 25, 2021
FDA (US Food and Drug Administration). Magnets in Cell Phones and Smart Watches May Affect Pacemakers and Other Implanted Medical Devices. FDA 2021
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