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What’s New in the Patient Safety World

July 2020


·       Not Following Medication Changes after Hospitalization?

·       Medication Dosage Miscalculations

·       Getting a Grip on Things

·       Patient Requests for EHR Corrections




Not Following Medication Changes after Hospitalization?



Medication reconciliation at any transition of care is important. But none are more critical that at the time of hospital discharge. Medication reconciliation at the time of discharge is different because the patient or his/her caregiver, rather than the hospital, is now responsible for ensuring any changes made to medications are adhered to. And we’ve often discussed how discharge is a very vulnerable time for patients. They are often so anxious to go home that they may not pay full attention to discharge instructions and thus may not fully understand any changes to their medication regimen.


That’s why the phone call (by a pharmacist, nurse, or physician) 24-48 hours after discharge is so important in ensuring patients understand those changes and will be adherent to the new medication regimen.


A new study (Weir 2020) addressed the impact of nonadherence to medication changes made at hospital discharge. The researchers found that 44% of 2655 patients were nonadherent to at least one medication change, and 32% were readmitted to hospital, visited the emergency department, or died in the 30 days post-discharge. Patients who were not adherent to any of their medication changes had a 35% higher risk of adverse events (after adjustment for confounders) compared to those who were adherent to all medication changes. Those who were adherent to some of their medication changes at discharge had a 10% elevated risk of adverse events in 30 days post-discharge compared to those who were adherent to all medication changes.


The impact of nonadherence on adverse events was mainly driven by not filling newly prescribed medications. There was no increased risk for nonadherence to discontinuations or dosage changes.


These were mostly elderly patients. The mean age of study patients was 69.5 years old. The study conclusions are somewhat limited because dispensing data was used to determine nonadherence. That could lead to erroneous conclusions if patients filled their prescriptions but did not take them or did not fill them but used existing supplies. Also, it is difficult to accurately assess doses from dispensing data (eg. patients could be pill-splitting). But, even given these limitations, the conclusions of the study are pretty compelling: we need to do a better job of not only performing accurate medication reconciliation at discharge but also ensuring adherence to changes made.


But such nonadherence should be anticipated. In our June 30, 2020 Patient Safety Tip of the Week “What Happens after Hospitalization?” we cited a study (Dharmarajan 2020) that showed disability in specific functional activities important to leaving home to access care and self‐managing health conditions is common, often new, and present for prolonged time periods after hospitalization for acute medical illness. One of those activities was taking medications. The researchers found that the proportion of patients newly disabled at 1 month after hospitalization for acute medical illness was 30% for taking medications.


Many patients following hospitalization have cognitive deficits or other impairments of activities of daily living that lead to medication nonadherence. We must anticipate those deficits and, therefore, work with caregivers to help improve adherence.


Previous research by these same authors (Weir 2019) suggested that failure to follow medication changes was highest for dose increases, symptom relief medications, those that require prior authorization, and medications that had not been administered during the hospital stay. At the patient level, those with at least one preadmission hospitalization, who did not have any medications dispensed prior to admission, and were discharged from thoracic surgery or to a long-term care facility, also had a higher risk of failure to follow changes.


There were 10,068 medication changes made at hospital discharge and 24% were not followed in the 30 days post discharge. Thirty percent of dose modifications were filled at the incorrect dose, 27% of new medications were not filled, and 12% of discontinued medications were filled. Factors associated with increased the risk of failure to follow medication changes were: increasing out-of-pocket medication costs (adjusted odds ratio 1.12), discharge to long-term care facility (aOR 2.29), and not having medications dispensed prior to admission (aOR 4.67).


Both Weir studies come out of hospitals in Montreal, Quebec.



Some of our previous columns on medication reconciliation:


October 23, 2007 “Medication Reconciliation Tools”

December 30, 2008 “Unintended Consequences: Is Medication Reconciliation Next?”

May 13, 2008 “Medication Reconciliation: Topical and Compounded Medications”

September 8, 2009 “Barriers to Medication Reconciliation”

August 2011 “The Approach to Medication Reconciliation”

January 2012 “AHRQ’s New Medication Reconciliation Tool Kit”

September 2012 “Good News on Medication Reconciliation”

October 1, 2019 “Electronic Medication Reconciliation: Glass Half Full or Half Empty?”






Weir DL, Motulsky A, Abrahamowicz M, et al. Failure to follow medication changes made at hospital discharge is associated with adverse events in 30 days. Health Serv Res 2020; 00: 1-12



Dharmarajan K, Han L, Gahbauer EA, Leo‐Summers LS, Gill TM. Disability and Recovery After Hospitalization for Medical Illness Among Community‐Living Older Persons: A Prospective Cohort Study. J Am Geriatr Soc 2020; 68: 486-495 Published online February 21, 2020



Weir DL, Motulsky A, Abrahamowicz M, et al. Challenges at care transitions: failure to follow medication changes made at hospital discharge. Am J Med 2019; 132: 1216-1224.e5





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Medication Dosage Miscalculations



Ah! Calculations! Talk about setting the stage for errors. Any time you have to calculate a drug dose, you are potentially vulnerable to error. You can enter wrong decimal points, use the wrong units, or simply make a mathematic mistake.


We’ve done several columns (listed below) on errors made in relation to patient weights. Most often that happens when a dose is calculated using a patient’s weight in pounds rather than kilograms. We’ve also discussed many examples of errors made in calculating IV medication doses when units like milligrams and milliliters are confused.


One of our favorite slides we use in several presentations is one showing typical human error rates for a variety of industries. That shows an error rate of 0.03 for simple arithmetic errors. That number comes from Park (Park 2012) in an earlier edition that is apparently no longer available. Smith (Smith 2005) had also noted studies show error rates in “doing arithmetic wrongly” to range from 0.01 to 0.03.


A recent article (Ressler 2020) notes that medication dosage miscalculations are, unfortunately, common and often go unnoticed. Prescriptions can be filled incorrectly by simply missing one crucial piece of information, like weight, or applying a proportion calculation incorrectly.


Ressler provides several examples of how such calculation errors can happen and how one error may even be compounded by a second error.


One example included the dosage of a drug being erroneously calculated based on weight in pounds, not kilograms and then the dosage was supposed to be split evenly every 12 hours but was instead prescribed to receive the full amount twice daily. The result was the incorrect calculation led to a dosage over four times higher than the intended dose.


Another example illustrates how incorrect dopamine concentration in a calculation led to potential overdose of this drug in a critical situation.


There’s even an example of how an incorrect calculation led to a pharmacy having a chargeback from Medicare Part D because of overbilling.


The article provides a link to an infographic the author suggests you hang in your pharmacy or classroom for these three scenarios that can help you illustrate the impact of a miscalculation.


Calculation of drug doses, particularly for high alert medications, is one process that may benefit from double checks. However, it is critical that those double checks be truly independent double checks.



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 Consequences”

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?”

June 2018                    “Incorrect Weights in the EMR”



Some of our other columns on double checks:


January 2010               “ISMP Article on Double Checks”

October 26, 2010        “Confirming Medications During Anesthesia”

October 16, 2012        “What is the Evidence on Double Checks?”

December 9, 2014       “More Trouble with NMBA’s”

April 19, 2016             “Independent Double Checks and Oral Chemotherapy”

December 11, 2018     “Another NMBA Accident”

March 5, 2019             “Infusion Pump Problems”

August 27, 2019         “Double Check on Double Checks”






Park K. Human Error, in Salveny G, ed.. Handbook of Human Factors and Ergonomics. Fourth Edition. Wiley 2012



Smith DJ. ‘Reliability, Maintainability and Risk” 7th Edition. Elsevier 2005



Ressler K. Bad Math: The Impact of Medication Dosage Miscalculations. Pharmacy Times 2020; June 8, 2020








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Getting a Grip on Things



We neurologists often take pride in being able to say we have completed half the neurological exam before the patient even sits down in our office. As the patient enters the room, we observe his stance and gait, gait speed, arm swing, any tremor or abnormal movements, and facial expression. As we introduce ourselves we get at least a glimpse of the patient’s speech articulation and prosody, if not a glimpse of a possible aphasia. And we usually shake hands with the patient (at least in the pre-COVID19 era!). The latter is, of course, a relatively subjective measure of grip strength. But, more and more, we have realized that formal measurement of grip strength provides a very powerful indicator of many patient vulnerabilities.


There are many parameters that have been used in various frailty indices (see our many columns on frailty listed below). Handgrip strength is one of those. In our June 2015 What's New in the Patient Safety World column “Get a Grip on It!” we noted that grip strength not only predicts surgical complications and outcomes but also predicts risk for stroke, MI, cardiovascular and all-cause death.


In an analysis of 351 consecutive patients undergoing major intra-abdominal operations Revenig and colleagues (Revenig 2015) found that “shrinking” and grip strength alone hold the same prognostic information as the full 5-component Fried Frailty Criteria for 30-day morbidity and mortality. When combined with American Society of Anesthesiologists (ASA) score and serum hemoglobin, they form a simple risk classification system with robust prognostic information.


Shortly after that publication, the results of the Prospective Urban-Rural Epidemiology (PURE) study were released (Leong 2015). This was a longitudinal population study done on approximately 140,000 subjects in 17 countries of diverse cultural and socioeconomic settings. Grip strength was measured with a dynamometer. Grip strength was inversely associated with all-cause mortality (16% increase for each 5 kg reduction in grip strength), cardiovascular mortality (17%), non-cardiovascular mortality (17%), myocardial infarction (7%), and stroke (9%). Grip strength was actually a stronger predictor of all-cause and cardiovascular mortality than systolic blood pressure.


In our May 16, 2017 Patient Safety Tip of the Week “Are Surgeons Finally Ready to Screen for Frailty?” we noted a study that looked at individual components of the Fried frailty phenotype measures (gait speed, hand-grip strength as measured by a dynamometer, and self-reported exhaustion, low physical activity, and unintended weight loss) in a primary care setting (Lee 2017). The researchers found that individual criteria all showed sensitivity and specificity of more than 80%, with the exception of weight loss. The positive predictive value of the single-item criteria in predicting the Fried frailty phenotype ranged from 12.5% to 52.5%. When gait speed and hand-grip strength were combined as a dual measure, the positive predictive value increased to 87.5%. They conclude that, while use of gait speed or grip strength alone was found to be sensitive and specific as a proxy for the Fried frailty phenotype, use of both measures together was found to be accurate, precise, specific, and more sensitive than other possible combinations and that assessing both measures is feasible within the primary care setting.


Analysis of data on over 500,000 patients in the UK (Celis-Morales 2018) found that reduced grip strength was associated with worse cardiovascular, respiratory, and cancer outcomes and all-cause mortality.


Probably the most extensive review of the literature on handgrip strength was done by Bohannon (Bohannon 2019). He concluded that there is adequate evidence to support the use of grip strength as an explanatory or predictive biomarker of specific outcomes such as generalized strength and function, bone mineral density, fractures, and falls, nutritional status, disease status and comorbidity load, cognition, depression, and sleep, hospital-related variables, and mortality. He suggested routine implementation of the measurement of grip strength for older adults in the community and healthcare settings.


Handgrip strength was a predictor of falls in the study by Xue (Xue 2011) and the review by Bohannon (Bohannon 2019). A recent article in Medscape (Millard 2020) discussed a study from Brazil that was scheduled to be presented at the recently cancelled American College of Sports Medicine (ACSM) 2020 Annual Meeting. The study of 204 elderly women found that the risk for falls was 2.73 times higher in women who had poor handgrip strength than in those who had normal handgrip strength. The risk was even greater in women with impaired balance.


But there are 2 additional important parameters on grip strength that we need to take into consideration:


The Women's Health and Aging Study (Xue 2011) found that a decline in grip strength over time is a stronger predictor of a greater variety of subsequent adverse outcomes compared with a single observation of grip strength, Outcomes included falls, walking speed slower than 0.4 m/s, the WHAS frailty phenotype, and difficulty in 1 or more task of the Activities of Daily Living (ADL) and Instrumental Activities of Daily Living (IADL) scales. Independent of baseline grip strength, a greater rate of decline in grip strength over time, was significantly associated with higher risk for all outcomes except ADL disability. The risk of developing an IADL disability was 1.32 times higher for every 0.5-SD unit increase in the rate of decline in grip strength. The associations were independent of age, disease burden, lifestyle, nutritional status, inflammation, and mental well-being. That led the authors to suggest that “becoming weaker” is important in addition to “being weak.”


A new study evaluated both grip strength (HGS) and asymmetry of grip strength in relation to cognitive function (McGrath 2020). McGrath and colleagues used a dynamometer to measure grip strength in elderly patients. Asymmetry was considered as any difference of more than 10% between sides. They found that weakness of grip strength and asymmetry of grip strength (even without weakness) were both predictive of lower cognitive function. Relative to those with symmetric HGS and no weakness, each HGS asymmetry and weakness group had greater odds for lower cognitive functioning: 1.15 for any HGS asymmetry alone, 1.64 for weakness alone, and 1.95 for any HGS asymmetry and weakness. Each HGS asymmetry dominance and weakness group also had greater odds for lower cognitive functioning: 1.12 for asymmetric dominant HGS alone, 1.27 for asymmetric nondominant HGS alone, 1.64 for weakness alone, 1.89 for weakness and asymmetric dominant HGS, and 2.10 for weakness and asymmetric nondominant HGS.


Measurement of handgrip strength is a simple, inexpensive way to identify patients who are at risk for frailty and a variety of adverse health outcomes. Reduced grip strength (and also asymmetric handgrip strength or worsening handgrip strength over time) is a marker for patients having multiple comorbidities that collectively reduce their physiologic reserve and make them more vulnerable to adverse outcomes. It can be used to predict increased risk for complications in patients undergoing surgery, predict patients at risk for falls, and many other conditions.



Some of our prior columns on preoperative assessment and frailty:






Revenig LM, Canter DJ, Kim S, et al. Report of a Simplified Frailty Score Predictive of Short-Term Postoperative Morbidity and Mortality. J Am Coll Surg 2015; 220(5): 904-911



Leong DP, Teo KT, Rangarajan S, et al. Prognostic value of grip strength: Findings from the Prospective Urban Rural Epidemiology (PURE) study. Lancet 2015; 386(9990): 266-273, July 18, 2015



Lee L, Patel T, Costa A, Bryce E, Hillier LM, Slonim K, et al. Screening for frailty in primary care. Accuracy of gait speed and hand-grip strength. Can Fam Physician 2017; 63: e51-7



Celis-Morales Carlos A, Welsh Paul, Lyall Donald M, Steell Lewis, Petermann Fanny, Anderson Jana et al. Associations of grip strength with cardiovascular, respiratory, and cancer outcomes and all cause mortality: prospective cohort study of half a million UK Biobank participants BMJ 2018; 361 :k1651



Bohannon R. W. (2019). Grip Strength: An Indispensable Biomarker For Older Adults. Clinical Interventions in Aging 2019; 14: 1681-1691



Xue Q, Walston JD, Fried LP, Beamer BA. Prediction of Risk of Falling, Physical Disability, and Frailty by Rate of Decline in Grip Strength: The Women's Health and Aging Study. Arch Intern Med 2011; 171(12): 1119-1121



Millard E. Handgrip Strength Could Be a Simple Way to Predict Fall Risk. Medscape Medical News 2020; June 10, 2020



McGrath R, Cawthon PM, Cesari M, et al. Handgrip Strength Asymmetry and Weakness Are Associated with Lower Cognitive Function: A Panel Study. J Am Geriatr Soc 2020; first published 30 May 2020





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Patient Requests for EHR Corrections



Your own electronic health record (EHR) says you are allergic to penicillin. You are not, in fact, allergic to penicillin. Yet, you might at some time in the future be denied appropriate use of penicillins or other antibiotics cross-reacting with penicillin.


You once received a trial of amitriptyline for a neuropathic condition. An intern, after review of your medication list, assumed you received it for depression and added depression to the problem list in your EHR. Physicians might avoid prescribing medications to you in the future that are contraindicated in patients with a history of depression.


A pharmacy error incorrectly listed digoxin in your medication list. As a result, a health care provider added congestive heart failure to your problem list. A whole host of medications may be contraindicated in patients with heart failure and physicians might avoid prescribing some of those that might be of benefit to you.


Inclusion of erroneous information in the EHR can have important patient safety implications. The presence of erroneous information in the EHR may be more prevalent than you think. In a 2017 study of the OpenNotes movement (Bell 2017), patients and care partners reported potential safety concerns in about one-quarter of reports, often resulting in a change to the record or care. Patients and care partners documented potential safety concerns in 23% of reports. 2% of patients did not understand the care plan and 21% reported possible mistakes, including medications, existing health problems, something important missing from the note or current symptoms. Among these, 64% were definite or possible safety concerns on clinician review, and 57% of cases confirmed with patients resulted in a change to the record or care.


In a more recent survey of almost 30,000 respondents (Bell 2020), 21.1% of patients who read a note reported finding a mistake in their EHR and 42.3% perceived the mistake as serious. The most common mistakes were perceived in current or past diagnoses (27.5%), medical history (23.9%), medications or allergies (14.0%), physical examination, and tests, procedures, or results (8.4%). Notably, 6.5% reflected notes reportedly written on the wrong patient. Of very serious errors, 58.9% included at least 1 perceived error potentially associated with the diagnostic process (eg, history, physical examination, tests, referrals, and communication).


Older and sicker patients were twice as likely to report a serious error compared with younger and healthier patients, indicating important safety and quality implications. The authors conclude that sharing notes with patients may help engage them to improve record accuracy and health care safety together with practitioners.


So, it’s pretty clear that mistakes in the EHR are both alarmingly frequent and potentially dangerous. Encouraging patients to access their medical records could go a long way toward avoiding potentially serious consequences.


HIPAA, of course, mandates that patients have access to their medical records. It also has a provision that patients may request a change, or amendment, to their record. The health care provider or health plan must respond to such requests (Heath 2019). The health care provider or health plan may, in some cases, deny changes to the medical record but the patient has the right to submit a statement of disagreement with such decisions into the medical record. The Heath article, though, notes that we should address such disagreements as possible communication gaps or signals that patient education may have fallen short. These should be considered as opportunities to improve the physician-patient relationship.


In a 2016 article (Klein 2016), Klein and colleagues pointed out that having patients read their patient encounters in their medical records provides many opportunities to improve care. Not only might that uncover errors in the medical record, it may also identify gaps in patient understanding of their diagnoses and/or treatment plan. So, in addition to improving patient safety, it may improve doctor-patient rapport. Klein et al. also note the importance of making notes clear and succinct, addressing concerns directly and respectfully, and using supportive language.


And encouraging patients to access their EHR’s can have a positive impact on health outcomes. Neves et al. (Neves 2020) recently performed a systematic review and meta-analysis on this issue. They found a beneficial effect in effectiveness by reducing absolute values of HbA1c. A significant reduction of absolute values of systolic blood pressure was also found but lost in sensitivity analysis for studies with low risk of bias. Regarding efficiency of care, 80% of studies found either a reduction of healthcare usage or no change. A beneficial effect was observed in a range of safety outcomes (ie, general adherence, medication safety), but not in medication adherence.


While 90% of healthcare providers offer patient portals, only about a third of patients actually access the portals (GAO 2017). While, on average, hospitals gave 95 percent of discharged patients access to view, download, and transmit their information, only about 10% of patients access their medical records (Lin 2019). A recent Health Affairs Blog (Bechtel 2020) posits that patient demand is not the reason for low rates of accessing EHR’s and describes barriers to access and potential ways to increase such access.


So, we are probably missing good opportunities to make our EHR’s more accurate and to improve on communication and our relationships with our patients.







Bell SK, Gerard M, Fossa A, et al. A patient feedback reporting tool for OpenNotes: implications for patient-clinician safety and quality partnerships. BMJ Quality & Safety 2017; 26: 312-322



Bell SK, Delbanco T, Elmore JG, et al. Frequency and Types of Patient-Reported Errors in Electronic Health Record Ambulatory Care Notes. JAMA Netw Open. 2020; 3(6): e205867



Heath S. Understanding Patient Requests for EHR Corrections, Changes. PatientEngagementHIT 2019; accessed December 3, 2019


Klein JW, Jackson SL, Bell SK, et al. Your Patient Is Now Reading Your Note: Opportunities, Problems, and Prospects. The American Journal of Medicine 2016; 129(10): 1018-1021



Neves AL, Freise L, Laranjo L, et al. Impact of providing patients access to electronic health records on quality and safety of care: a systematic review and meta-analysis. BMJ Quality & Safety 2020; Published Online First: 12 June 2020



GAO (US Government Accountability Office) Health Information Technology:HHS Should Assess the Effectiveness of Its Efforts to Enhance Patient Access to and Use of Electronic Health Information. GAO-17-305: Published: Mar 15, 2017. Publicly Released: Mar 15, 2017



Lin SC, Lyles CR, Sarkar U, Adler-Milstein J. Are Patients Electronically Accessing Their Medical Records? Evidence From National Hospital Data. Health Affairs 2019; 38(11): November 2019



Bechtel C, Ricciardi L, deBronkart D, at al. Why Aren’t More Patients Electronically Accessing Their Medical Records? (Yet!). Health Affairs Blog 2020; January 13, 2020





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