Abstract
IMPORTANCE
The Patient Protection and Affordable Care Act of 2010 brought attention to adverse drug events in national patient safety efforts. Updated, detailed, nationally representative data describing adverse drug events can help focus these efforts.
OBJECTIVE
To describe the characteristics of emergency department (ED) visits for adverse drug events in the United States in 2013-2014 and describe changes in ED visits for adverse drug events since 2005-2006.
DESIGN, SETTING, AND PARTICIPANTS
Active, nationally representative, public health surveillance in 58 EDs located in the United States and participating in the National Electronic Injury Surveillance System–Cooperative Adverse Drug Event Surveillance project.
EXPOSURES
Drugs implicated in ED visits.
MAIN OUTCOMES AND MEASURES
National weighted estimates of ED visits and subsequent hospitalizations for adverse drug events.
RESULTS
Based on data from 42 585 cases, an estimated 4.0 (95% CI, 3.1-5.0) ED visits for adverse drug events occurred per 1000 individuals annually in 2013 and 2014 and 27.3% (95% CI, 22.2%-32.4%) of ED visits for adverse drug events resulted in hospitalization. An estimated 34.5% (95% CI, 30.3%-38.8%) of ED visits for adverse drug events occurred among adults aged 65 years or older in 2013-2014 compared with an estimated 25.6% (95% CI, 21.1%-30.0%) in 2005-2006; older adults experienced the highest hospitalization rates (43.6%; 95% CI, 36.6%-50.5%). Anticoagulants, antibiotics, and diabetes agents were implicated in an estimated 46.9% (95% CI, 44.2%-49.7%) of ED visits for adverse drug events, which included clinically significant adverse events, such as hemorrhage (anticoagulants), moderate to severe allergic reactions (antibiotics), and hypoglycemia with moderate to severe neurological effects (diabetes agents). Since 2005-2006, the proportions of ED visits for adverse drug events from anticoagulants and diabetes agents have increased, whereas the proportion from antibiotics has decreased. Among children aged 5 years or younger, antibiotics were the most common drug class implicated (56.4%; 95% CI, 51.8-61.0%). Among children and adolescents aged 6 to 19 years, antibiotics also were the most common drug class implicated (31.8%; 95% CI, 28.7%-34.9%) in ED visits for adverse drug events, followed by antipsychotics (4.5%; 95% CI, 3.3-5.6%). Among older adults (aged ≥65 years), 3 drug classes (anticoagulants, diabetes agents, and opioid analgesics) were implicated in an estimated 59.9% (95% CI, 56.8%-62.9%) of ED visits for adverse drug events; 4 anticoagulants (warfarin, rivaroxaban, dabigatran, and enoxaparin) and 5 diabetes agents (insulin and 4 oral agents) were among the 15 most common drugs implicated. Medications to always avoid in older adults according to Beers criteria were implicated in 1.8% (95% CI, 1.5%-2.1%) of ED visits for adverse drug events.
CONCLUSIONS AND RELEVANCE
The prevalence of emergency department visits for adverse drug events in the United States was estimated to be 4 per 1000 individuals in 2013 and 2014. The most common drug classes implicated were anticoagulants, antibiotics, diabetes agents, and opioid analgesics.
Adverse drug events are the most common cause of iatrogenic harm in health care and have recently received attention in national patient safety initiatives. The Patient Protection and Affordable Care Act of 2010 incentivized new programs that target adverse drug event prevention within hospitals and during care transitions between inpatient and outpatient settings. However, in outpatient settings, in which 90% of US prescription drug expenditures occur,1 preventing adverse drug events remains a public health and patient safety challenge, with efforts often focused on medication errors and reducing potentially inappropriate prescribing for older adults (aged ≥65 years) as defined by the Beers criteria.2,3 Patients in ambulatory care and some postacute care settings can have complex medication regimens, at times prescribed by multiple clinicians, with far less monitoring compared with hospitalized patients.
The US Centers for Disease Control and Prevention collaborates with the US Consumer Product Safety Commission and the US Food and Drug Administration to conduct active, nationally representative public health surveillance for outpatient adverse drug events resulting in emergency department (ED) visits.4 The purpose of this study was to describe ED visits for adverse drug events in 2013-2014 to help advance medication safety initiatives for outpatient settings.
Methods
Data Sources and Data Collection Methods
The National Electronic Injury Surveillance System-Cooperative Adverse Drug Event Surveillance (NEISS-CADES) project is an active public health surveillance system based on a nationally representative, size-stratified probability sample of US hospitals (excluding psychiatric and penal institutions) that have a minimum of 6 beds and a 24-hour emergency department, with 4 strata based on hospital size (assessed by the total number of annual ED visits), and 1 pediatric hospital stratum.5 Since 2004, between 58 and 63 hospitals have participated in the NEISS-CADES project.
As described previously,4 trained Consumer Product Safety Commission data abstractors at each hospital review the clinical records of every ED visit to identify any clinician-diagnosed adverse drug events that are the reason for the ED visit, and report up to 2 medications implicated in the adverse event, as well as any concomitant medications documentedin the medical record. Abstractors also record narrative descriptions of adverse drug events, including preceding events, clinician diagnosis or clinical impression, “chief complaint,” clinical and laboratory testing, treatments administered in the ED or by emergency medical services, and discharge disposition.
Reports were coded by the Centers for Disease Control and Prevention using the Medical Dictionary for Regulatory Activities version 9.1 to describe diagnosis, symptoms, and, if documented, medication errors. Names of implicated drugs were standardized to active ingredients. Data collection from the NEISS-CADES project hospitals has been deemed a public health surveillance activity by the Centers for Disease Control and Prevention human subject oversight bodies and did not require institutional review board approval.6
Definitions
Cases included ED visits in which prescription or over-the-counter medications, dietary supplements (eg, herbals, vitamins, or minerals), homeopathic products, or vaccines were implicated in the adverse events. Adverse drug events were classified as adverse effects, allergic reactions, supratherapeutic effects or excess dose, secondary effects (such as choking or injection site reactions), unsupervised ingestion by a child, or vaccination reactions. Drug withdrawal, drug therapeutic failures, occupational exposures, intentional self-harm, recreational drug use or abuse, and adverse events from treatments received in the ED were excluded. Follow-up visits for previously diagnosed adverse drug events and deaths in or en route to the ED also were excluded.
Potentially inappropriate medications for older adults included all drugs in the American Geriatrics Society’s 2015 updated Beers criteria for potentially inappropriate medication use, except for insulin (inappropriate in sliding scale doses) and aspirin (inappropriate at doses >325 mg/d).3 Potentially inappropriate medications to “always avoid” (the most common adaptation of the Beers criteria in national health care quality measures7,8) included drugs considered potentially inappropriate for any indication or in any dose, duration, or formulation, such as first-generation antihistamines, skeletal muscle relaxants, and short- and intermediate-acting benzodiazepines.
Medication errors included (1) administration of incorrect drugs; (2) incorrect dose, schedule, rate, duration, or site of drug administration (including accidental needle stick); and (3) administration of expired medications, old prescriptions, or use of medications prescribed or belonging to another individual. Hospitalization was defined as admission to the inpatient setting, observation status admission, or transfer to another facility.
Statistical Analysis
Each case from the NEISS-CADES project was assigned a sample weight based on hospital sampling design and inverse probability of selection.5 Weights were adjusted for brief periods of nonresponse and poststratified to account for changes in the total number of ED visits each year in the United States.5 Adverse drug event population rates were calculated using population estimates from the US Census Bureau; population estimates were considered free of sampling error.9 Nationally projected (estimated) proportions of ED visits and hospitalizations with corresponding 95% CIs were calculatedusing the SURVEYMEANS procedure in SAS version 9.3 (SAS Institute Inc) to account for sample weights and complex sample design.
Estimates based on small numbers of cases (<20) are considered statistically unreliable and are not shown. Estimates with a coefficient of variation greater than 30% may be statistically unreliable and are noted. Select estimated population rates and proportions of ED visits for adverse drug events in 2013-2014 were compared with estimates from 2005-2006.
Results
Based on 42 585 cases, there were an estimated 4.0 (95% CI, 3.1-5.0) ED visits for adverse drug events per 1000 individuals annually in the United States in 2013-2014. An estimated 34.5% (95% CI, 30.3%-38.8%) of ED visits for adverse drug events occurred in older adults (aged ≥65 years) in 2013-2014 (Table 1) compared with an estimated 25.6% (95% CI, 21.1%-30.0%) in 2005-2006 (eTable 1 in the Supplement). The population rate of ED visits for adverse drug events among older adults (aged ≥65 years) was 9.7 (95% CI, 6.6-12.9) visits per 1000 individuals compared with 3.1 (95% CI, 2.6-3.6) visits per 1000 individuals for those younger than 65 years.
Table 1.
ED Visits for ADEs |
ED Visits for ADEs Resulting in Hospitalizationb |
|||
---|---|---|---|---|
Case Characteristic | No. of Cases | National Estimate, % (95% CI)c |
No. of Cases Hospitalized |
National Estimate, % Hospitalized (95% CI)c |
Patient age group, yd | ||||
≤5 | 5133 | 9.7 (7.7-11.6) | 846 | 10.5 (7.7-13.2) |
6-19 | 3452 | 6.8 (5.7-7.9) | 571 | 8.9 (5.4-12.4) |
20-34 | 5638 | 13.7 (12.4-15.0) | 667 | 10.2 (7.3-13.2) |
35-49 | 5928 | 14.3 (13.0-15.6) | 1230 | 18.5 (14.2-22.8) |
50-64 | 8797 | 21.0 (19.4-22.6) | 3003 | 31.4 (25.9-37.0) |
65-79 | 8266 | 21.1 (18.6-23.7) | 3563 | 41.1 (33.8-48.3) |
≥80 | 5370 | 13.4 (11.3-15.5) | 2718 | 47.5 (40.7-54.3) |
Patient sex | ||||
Female | 23 934 | 57.1 (55.6-58.7) | 6754 | 25.8 (21.1-30.4) |
Male | 18 651 | 42.9 (41.3-44.4) | 5844 | 29.3 (23.6-35.1) |
No. of implicated medications | ||||
1 | 35 142 | 83.8 (81.5-86.1) | 9716 | 25.7 (20.8-30.6) |
≥2 | 7443 | 16.2 (13.9-18.5) | 2882 | 35.7 (29.4-42.0) |
Type ofADE | ||||
Adverse effecte | 12 081 | 27.8 (24.9-30.7) | 3957 | 29.4 (23.2-35.5) |
Allergic reaction (immunologically mediated effects) | 10 435 | 26.0 (23.5-28.6) | 1080 | 9.2 (6.3-12.0) |
Supratherapeutic effect of a drug or ingestion of excess dose | 15 718 | 37.2 (34.7-39.6) | 6835 | 42.1 (35.6-48.7) |
Secondary effectf | 835 | 2.0 (1.7-2.3) | 94 | 11.9 (8.5-15.3) |
Unsupervised ingestion bya childg | 2604 | 4.9 (3.8-5.9) | 590 | 16.6 (12.4-20.7) |
Vaccination reaction (anyadverse effect from a vaccine) | 912 | 2.2 (1.7-2.6) | 42 | 2.9 (1.6-4.3) |
Documented medication errorh | ||||
Yes | 4747 | 10.5 (8.8-12.2) | 1205 | 24.6 (19.3-29.9) |
No | 37 838 | 89.5 (87.8-91.2) | 11393 | 27.6 (22.4-32.8) |
Total | 42 585 | 100.0 | 12 598 | 27.3 (22.2-32.4) |
Data are from the National Electronic Injury Surveillance System–Cooperative Adverse Drug Event Surveillance project, US Centers for Disease Control and Prevention. Cases included ED visits for ADEs from prescription or over-the-counter medications, dietary supplements, homeopathic products, and vaccines. Visits to the ED involving drug withdrawal, drug therapeutic failures, occupational exposures, intentional self-harm, and recreational drug use or abuse were excluded. Adverse events from treatments received in the ED, follow-up visits for previously diagnosed ADEs, and deaths in or en route to the ED also were excluded.
Defined as hospital admission, observation status admission, or transfer to another facility. Discharge disposition missing for 1 case.
Calculated from statistical weighting of cases based on the sample design.
Missing for 1 case.
Defined as undesirable pharmacological or idiosyncratic effects at recommended doses.
Refers to other adverse effects secondary to drug administration such as choking or injection site reactions.
Refers to children aged 10 years or younger ingesting or being found with medications without caregiver supervision.
Refers to drug prescribing, dispensing, or administration errors (eg, wrong drug, wrong dose, wrong duration, wrong route, expired drug, or old prescription), administration of another individual's medication, or accidental needle stick in individuals aged 11 years or older.
Compared with 2005-2006, population rates of ED visits for adverse drug events increased among older adults aged 65 years or older (5.2 [95% CI, 3.2-7.2] visits per 1000 individuals in 2005-2006 vs 9.7 [95% CI, 6.6-12.9] visits per 1000 individuals in 2013-2014) and among adults aged 50 years to 64 years (2.5 [95% CI, 1.8-3.1] visits per 1000 individuals in 2005-2006 vs 4.3 [95% CI, 3.3-5.3] visits per 1000 individuals in 2013-2014), whereas population rates for other age groups were similar for both periods (eTable 2 in the Supplement). More ED visits for adverse drug events involved females (57.1%; 95% CI, 55.6%-58.7%).
A single medication was implicated in most ED visits for adverse drug events (83.8%; 95% CI, 81.5%-86.1%). Supra-therapeutic effects or ingestion of excess dose was the most common type of adverse drug event (37.2%; 95% CI, 34.7%-39.6%). Medication errors were documented in 1 of 10 ED visits for adverse drug events (10.5%; 95% CI, 8.9%-12.2%).
An estimated 27.3% (95% CI, 22.2%-32.4%) of ED visits for adverse drug events resulted in hospitalization. Hospitalization rates were highest for older adults (aged ≥65 years), of whom an estimated 43.6% (95% CI, 36.6%-50.5%) were hospitalized. When adjusted for the US population, the hospitalization rate for adverse drug events among adults aged 65 years or older was 7 times higher (4.2 [95% CI, 2.5-6.0] hospitalizations per 1000 individuals) than for those younger than 65 years (0.6 [95% CI, 0.4-0.8] hospitalizations per 1000 individuals).
In 2013-2014, the most commonly implicated drug classes were anticoagulants (17.6%), systemically administered (oral or injectable) antibiotics (16.1%), diabetes agents (13.3%), opioid analgesics (6.8%), antiplatelets (6.6%), renin-angiotensin system inhibitors (3.5%), antineoplastic agents (3.0%), and sedative or hypnotic agents (3.0%) (Table 2). The top 3 drug classes (anticoagulants, antibiotics, and diabetes agents) were implicated in an estimated 46.9% (95% CI, 44.2%-49.7%) of ED visits for adverse drug events. Since 2005-2006, the proportions of ED visits for adverse drug events involving anticoagulants, antiplatelets, and diabetes agents have increased, whereas the proportion involving antibiotics has decreased (eTable 3 in the Supplement).
Table 2.
ED Visits for ADEs |
ED Visits for ADEs Resulting in Hospitalizationb |
|||
---|---|---|---|---|
Drug Class | No. of Cases | National Estimate, % (95% CI)c |
No. of Cases Hospitalized |
National Estimate, % Hospitalized (95% CI)c |
Hematologic Agents | ||||
Anticoagulants | 7211 | 17.6 (14.1-21.0) | 3691 | 48.8 (42.0-55.5) |
Vitamin K antagonists (warfarin) | 6179 | 15.1 (12.3-17.9) | 3156 | 48.5 (41.8-55.1) |
Factor Xa inhibitors | 580 | 1.4 (0.9-2.0) | 300 | 50.4 (43.0-57.8) |
Unfractionated and low-molecular-weight heparins | 450 | 0.8 (0.6-1.1) | 224 | 46.5 (38.7-54.4) |
Direct thrombin inhibitors (oral) | 173 | 0.5 (0.2-0.7) | 107 | 63.8 (49.8-77.8) |
Antiplatelets | 2656 | 6.6 (4.7-8.5) | 1312 | 44.4 (35.7-53.2) |
Platelet P2Y12 receptor antagonistsd | 1837 | 4.6 (3.0-6.2) | 942 | 47.8 (37.7-57.9) |
Aspirin with or without dipyridamole | 1545 | 3.6 (2.2-5.0) | 753 | 41.2 (32.6-49.8) |
Systemic Antimicrobial Agentse | ||||
Antibiotics | 6426 | 16.1 (14.4-17.8) | 481 | 7.1 (5.3-9.0) |
Amoxicillin-containing penicillins | 2198 | 4.8 (4.2-5.4) | 96 | 3.7 (2.3-5.2) |
Sulfonamide-containing agents | 1174 | 3.2 (2.7-3.7) | 108 | 8.9 (6.2-11.5) |
Cephalosporins | 776 | 2.0 (1.7-2.4) | 63 | 6.7 (4.2-9.2) |
Quinolones | 592 | 1.7 (1.4-1.9) | 77 | 14.5 (11.0-18.0) |
Erythromycins and macrolides | 410 | 1.2 (1.0-1.3) | 24 | 5.5 (2.6-8.3) |
Lincosamides (clindamycin) | 396 | 1.0 (0.8-1.2) | 28 | 5.5 (2.1-8.8) |
Tetracyclines | 286 | 0.7 (0.6-0.8) | 16 | NA |
Metronidazole | 195 | 0.4 (0.3-0.5) | 18 | NA |
Other antibiotics | 439 | 1.1 (0.9-1.3) | 68 | 12.1 (7.6-16.6) |
Antivirals and antiretrovirals | 148 | 0.3 (0.2-0.4) | 14 | NA |
Other systemic antimicrobial agents | 123 | 0.3 (0.2-0.4) | 16 | NA |
Hormone-Modifying Agents | ||||
Diabetes agents | 5995 | 13.3 (10.8-15.8) | 2314 | 38.5 (31.4-45.7) |
Insulin | 4859 | 10.7 (8.6-12.7) | 1692 | 34.8 (27.3-42.2) |
Oraldiabetes agents | 1595 | 3.6 (2.8-4.4) | 852 | 53.0 (46.6-59.5) |
Adrenocortical steroids | 480 | 1.2 (1.0-1.5) | 69 | 11.4 (6.1-16.6) |
Systemic and vaginal contraceptives | 279 | 0.5 (0.4-0.7) | 27 | 8.7 (2.9-14.5)f |
Other hormone-modifying agents | 302 | 0.7 (0.6-0.9) | 36 | 9.5 (5.7-13.2) |
Central Nervous System Agentsg | ||||
Analgesics | 3412 | 8.4 (7.7-9.1) | 878 | 23.6 (18.7-28.5) |
Opioid-containing analgesics | 2714 | 6.8 (6.3-7.4) | 729 | 24.6 (19.7-29.5) |
Oxycodone-containing analgesics | 856 | 2.0 (1.7-2.4) | 265 | 30.1 (25.2-35.1) |
Hydrocodone-containing analgesics | 614 | 1.7 (1.3-2.1) | 94 | 13.5 (9.0-18.0) |
Non-opioid-containing analgesicsh | 655 | 1.4 (1.1-1.7) | 145 | 20.0 (12.4-27.5) |
Sedative or hypnotic agents | 1218 | 3.0 (2.4-3.5) | 373 | 28.2 (19.9-36.4) |
Benzodiazepines | 822 | 2.0 (1.6-2.4) | 250 | 27.3 (19.1-35.4) |
Nonbenzodiazepine or nonbarbiturate sedativesi | 276 | 0.6 (0.4-0.8) | 87 | 33.2 (19.0-47.4) |
Antipsychotics | 1281 | 2.7 (2.1-3.2) | 320 | 25.3 (20.1-30.4) |
Antidepressants | 1045 | 2.6 (2.2-3.1) | 193 | 15.6 (10.9-20.4) |
Anticonvulsants | 1029 | 2.4 (2.1-2.7) | 344 | 30.4 (24.7-36.1) |
Stimulants | 339 | 0.7 (0.5-0.9) | 53 | 10.5 (6.4-14.6) |
Anesthetics (systemic) | 188 | 0.4 (0.3-0.5) | 32 | 15.5 (8.5-22.5) |
Other central nervous system agents | 364 | 0.9 (0.7-1.1) | 76 | 21.1 (14.7-27.5) |
Cardiovascular Agents | ||||
Renin-angiotensin system inhibitorsj | 1578 | 3.5 (2.6-4.4) | 516 | 31.9 (23.2-40.6) |
β-Blockers | 495 | 1.3 (1.0-1.6) | 186 | 38.1 (28.5-47.7) |
Calcium channelblockers | 317 | 0.8 (0.6-0.9) | 94 | 31.4 (24.3-38.5) |
Diuretics | 292 | 0.8 (0.6-1.0) | 112 | 40.8 (29.2-52.4) |
Centrally acting antiadrenergics | 232 | 0.4 (0.3-0.6) | 91 | 30.3 (19.5-41.0) |
Lipid-lowering agents | 124 | 0.3 (0.2-0.4) | 20 | 11.3 (3.4-19.2)f |
Digitalis glycosides (digoxin) | 116 | 0.3 (0.2-0.4) | 96 | 82.1 (74.0-90.3) |
Antianginals and antiarrhythmics | 121 | 0.3 (0.2-0.4) | 46 | 45.2 (28.4-61.9) |
Epinephrine (injection) | 150 | 0.3 (0.2-0.3) | 5 | NA |
Other cardiovascular agents | 179 | 0.4 (0.3-0.5) | 48 | 28.6 (16.6-40.6) |
Oncologicaland Immunologic Agents | ||||
Antineoplastic agents | 2007 | 3.0 (1.6-4.3) | 1303 | 59.7 (51.4-68.1) |
Immune modulatorsk | 182 | 0.3 (0.2-0.4) | 48 | 55.7 (47.2-64.3) |
Musculoskeletal Agents | ||||
Nonsteroidal anti-inflammatory drugsl | 1199 | 2.8 (2.4-3.2) | 174 | 12.6 (8.7-16.5) |
Skeletal muscle relaxants | 407 | 1.0 (0.8-1.2) | 111 | 24.7 (17.2-32.1) |
Respiratory Agents | ||||
Single-ingredient antihistamines | 603 | 1.3 (1.1-1.6) | 94 | 11.9 (6.9-17.0) |
Cough and cold remediesm | 533 | 1.3 (1.1-1.5) | 58 | 10.9 (7.7-14.1) |
Bronchodilators | 106 | 0.3 (0.2-0.3) | 6 | NA |
Gastrointestinal Agents | ||||
Antidiarrheals, laxatives, and antiflatulents | 219 | 0.6 (0.4-0.7) | 34 | 18.0 (10.1-25.9) |
Anti-ulcer and antacid agents | 202 | 0.4 (0.3-0.5) | 17 | NA |
Other gastrointestinal agents | 226 | 0.5 (0.4-0.6) | 30 | 11.7 (4.5-18.8)f |
Other Drug Classes | ||||
Vaccines | 916 | 2.2 (1.7-2.6) | 43 | 3.0 (1.7-4.3) |
Dermatologic agentsn | 458 | 1.1 (0.9-1.4) | 23 | 3.6 (1.1-6.1)f |
Radiopharmaceutical agents | 302 | 0.7 (0.5-0.9) | 44 | 10.9 (5.4-16.4) |
Ophthalmic, otic, and nasal agents | 266 | 0.6 (0.5-0.7) | 11 | NA |
Genitourinary agents | 163 | 0.4 (0.3-0.5) | 26 | 16.5 (10.1-22.8) |
Dietary Supplements and Related Products | ||||
Herbals (systemic and topical) and homeopathic agents | 488 | 1.2 (1.0-1.4) | 60 | 10.0 (6.4-13.5) |
Vitamins, minerals, trace elements, and combinations | 500 | 1.1 (0.9-1.3) | 69 | 12.9 (7.3-18.5) |
Other agents | 182 | 0.5 (0.4-0.6) | 21 | 9.0 (3.1-14.8)f |
Unknown agents | 681 | 1.8 (1.4-2.2) | 132 | 16.4 (11.4-21.4) |
Abbreviation: NA, estimates based on fewer than 20 cases are considered statistically unreliable and are not shown.
Data are based on 42 585 cases from the National Electronic Injury Surveillance System–Cooperative Adverse Drug Event Surveillance project, US Centers for Disease Control and Prevention. Specific drug classes are shown if they were implicated in 0.3% or greater of all estimated ED visits for ADEs in 2013-2014. Drug classes are not mutually exclusive. For some ED visits, a medication from more than 1 drug class was implicated in the ADE; therefore, percentages may total more than 100%.
Defined as hospital admission, observation status admission, or transfer to another facility.
Calculated from statistical weighting of cases based on the sample design.
Clopidogrel, prasugrel, ticagrelor, and ticlopidine.
Antibiotics in combination with anti-ulcer agents (eg, amoxicillin-clarithromycin-lansoprazole) are categorized asgastrointestinal agents.
Coefficient of variation greater than 30%.
Excludes ED visits for abuse or self-harm.
Excludes single-ingredient aspirin. Includes combination analgesic agents containing aspirin and combinations with antihistamines (eg, acetaminophen-diphenhydramine).
Eszopiclone, zaleplon, and zolpidem.
Single ingredient and in combination with diuretics (eg, hydrochlorothiazide-lisinopril) and calcium channel blockers (eg, amlodipine-benazepril).
Immunoglobulins, immune suppressants, interferons, and other immune modulators.
Includes nonsteroidal anti-inflammatory agents in combination with antihistamines (eg, ibuprofen-diphenhydramine).
Single-ingredient antitussives, decongestants, expectorants; and antitussives, decongestants, and expectorants in combination with antihistamines.
Topically administered agents and acne agents (systemically administered or topically administered).
Hospitalization rates were highest for ED visits for adverse drug events in which digitalis glycosides (82.1%), antineoplastic agents (59.7%), immune modulators (55.7%), oral diabetes agents (53.0%), andanticoagulants (48.8%) were implicated, and lowest for ED visits in which vaccines (3.0%), dermatologic agents (3.6%), and systemically administered antibiotics (7.1%) were implicated; however, the hospitalization rate for ED visits for adverse drug events from quinolone antibiotics was higher (14.5%) than the rates for all other antibiotic classes.
The most common drug products implicated in ED visits for adverse drug events varied by patient age (Table 3). Among children and adolescents aged 19 years or younger, the 15 most common drug products implicated were involved in an estimated 49.9% (95% CI, 46.8%-53.0%) of ED visits for adverse drug events, excluding unsupervised ingestions by children. Eight of the 15 most common drug products implicated in ED visits among children and adolescents aged 19 years or younger were antibiotics, and 2 were neuropsychiatric agents (methylphenidate and risperidone).
Table 3.
Drug Product | ED Visits for ADEs | |
---|---|---|
No. of Cases | National Estimate, % (95% CI)b | |
All Patients (N = 42 585) | ||
Warfarin | 6179 | 15.1 (12.3-17.9) |
Insulin | 4859 | 10.7 (8.6-12.7) |
Clopidogrel | 1778 | 4.4 (2.9-5.9) |
Amoxicillin | 1780 | 3.8 (3.3-4.3) |
Aspirin | 1518 | 3.5 (2.2-4.9) |
Sulfamethoxazole-trimethoprim | 1152 | 3.2 (2.7-3.7) |
Lisinopril | 1096 | 2.4 (1.8-3.0) |
Metformin | 766 | 1.7 (1.4-2.1) |
Ibuprofen | 722 | 1.6 (1.3-2.0) |
Rivaroxaban | 526 | 1.3 (0.8-1.8) |
Acetaminophen-hydrocodone | 492 | 1.3 (1.0-1.6) |
Cephalexin | 431 | 1.2 (0.9-1.5) |
Acetaminophen-oxycodone | 459 | 1.1 (0.8-1.4) |
Acetaminophen | 479 | 1.0 (0.8-1.2) |
Amoxicillin-clavulanate | 422 | 1.0 (0.9-1.2) |
Patients Aged ≤19 y (n = 5981)c | ||
Amoxicillin | 1264 | 21.5 (19.8-23.1) |
Sulfamethoxazole-trimethoprim | 244 | 5.3 (3.9-6.7) |
Ibuprofen | 173 | 3.6 (2.7-4.5) |
Azithromycin | 128 | 3.0 (2.5-3.6) |
Amoxicillin-clavulanate | 186 | 2.9 (2.3-3.5) |
Cefdinir | 153 | 2.6 (1.4-3.8) |
Cephalexin | 120 | 2.5 (1.7-3.3) |
Insulin | 106 | 1.7 (1.1-2.3) |
Acetaminophen | 81 | 1.6 (1.0-2.1) |
Clindamycin | 88 | 1.3 (0.9-1.8) |
Penicillin | 49 | 1.1 (0.6-1.5) |
Influenza vaccine | 58 | 1.0 (0.6-1.4) |
Methylphenidate | 51 | 0.9 (0.6-1.3) |
Diphenhydramine | 52 | 0.9 (0.5-1.3) |
Risperidone | 50 | 0.9 (0.4-1.3) |
Patients Aged ≥65 y (n = 13 636) | ||
Warfarin | 4397 | 31.9 (27.6-36.2) |
Insulin | 1950 | 13.0 (10.3-15.8) |
Clopidogrel | 1373 | 9.9 (7.3-12.5) |
Aspirin | 1052 | 7.1 (4.0-10.2) |
Rivaroxaban | 412 | 2.9 (2.1-3.8) |
Lisinopril | 380 | 2.6 (1.9-3.3) |
Metformin | 373 | 2.6 (2.0-3.2) |
Glipizide | 295 | 1.8 (1.3-2.4) |
Sulfamethoxazole-trimethoprim | 153 | 1.4 (1.1-1.7) |
Dabigatran | 154 | 1.2 (0.7-1.7) |
Acetaminophen-hydrocodone | 131 | 1.1 (0.8-1.4) |
Metoprolol | 105 | 1.0 (0.7-1.3) |
Enoxaparin | 179 | 1.0 (0.7-1.3) |
Glyburide | 131 | 1.0 (0.7-1.3) |
Glimepiride | 132 | 0.9 (0.6-1.2) |
Data are from the National Electronic Injury Surveillance System–Cooperative Adverse Drug Event Surveillance project, US Centers for Disease Control and Prevention. Data exclude ED visits for abuse or self-harm. Drug products are not mutually exclusive; for some ED visits, more than 1 drug product was implicated in the ADE. Drugs that were not identified at the active ingredient level (eg, unnamed antibiotic or unknown drug) are not shown.
Calculated from statistical weighting of cases based on the sample design. National estimates may vary for similar Nos. of cases because of statistical weighting.
Excludes ED visits for unsupervised medication ingestions by children aged 10 years or younger.
Among children aged 5 years or younger, antibiotics alone were the most common drug class implicated in ED visits for adverse drug events (56.4%; 95% CI, 51.8%-61.0%). Among children and adolescents aged 6 to 19 years, antibiotics were implicated in 31.8% (95% CI, 28.7%-34.9%) of ED visits for adverse drug events (Table 4 and eFigure in the Supplement). Antipsychotics alone were the second most common singly implicated drug class among children and adolescents aged 6 to 19 years comprising 4.5% (95% CI, 3.3%-5.6%) of estimated ED visits for adverse drug events. In this age group, at least 1 neuropsychiatric agent (anticonvulsant, antidepressant, antipsychotic, opioid analgesic, sedative or hypnotic agent, or stimulant) was implicated in an estimated 23.5% (95% CI, 21.1%-26.1%) of ED visits for adverse drug events.
Table 4.
ED Visits for ADEs |
||||||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Patient Age ≤5 yb |
Patient Age 6-19 yb |
Patient Age 20-34 y |
Patient Age 35-49 y |
Patient Age 50-64 y |
Patient Age 65-79 y |
Patient Age ≥80 y |
||||||||
Drug Class | No. of Cases (n = 2741) |
National Estimate, % (95% CI)c |
No. of Cases (n = 3240) |
National Estimate, % (95% CI)c |
No. of Cases (n = 5638) |
National Estimate, % (95% CI)c |
No. of Cases (n = 5928) |
National Estimate, % (95% CI)c |
No. of Cases (n = 8797) |
National Estimate, % (95% CI)c |
No. of Cases (n = 8266) |
National Estimate, % (95% CI)c |
No. of Cases (n = 5370) |
National Estimate, % (95% CI)c |
Antibiotics | 1460 | 56.4 (51.8-61.0) |
870 | 31.8 (28.7-34.9) |
1257 | 24.2 (21.5-26.9) |
873 | 16.2 (14.1-18.2) |
832 | 11.1 (9.8-12.4) |
447 | 6.3 (5.3-7.3) |
242 | 5.8 (4.5-7.0) |
Anticoagulants | 6 | NA | 13 | NA | 133 | 2.1 (1.6-2.6) |
454 | 7.2 (5.2-9.2) |
1240 | 13.7 (11.1-16.4) |
2233 | 27.5 (23.3-31.7) |
2206 | 38.8 (33.7-43.8) |
Antidepressants | 6 | NA | 107 | 3.8 (2.5-5.1) |
184 | 3.5 (2.6-4.3) |
157 | 2.7 (2.0-3.5) |
126 | 1.7 (1.2-2.1) |
55 | 0.8 (0.6-1.0) |
24 | 0.7 (0.1-1.3)d |
Antineoplastic agents | 283 | 2.8 (0-6.0)d |
330 | 2.7 (0-5.8)d |
106 | 1.3 (0.5-2.1)d |
196 | 2.3 (1.1-3.6) |
546 | 5.2 (3.1-7.4) |
384 | 3.6 (2.0-5.2) |
92 | 1.4 (0.7-2.1) |
Antiplatelets | 1 | NA | 16 | NA | 37 | 0.5 (0.3-0.7) |
68 | 1.3 (0.7-1.9) |
359 | 4.3 (3.1-5.5) |
657 | 8.0 (5.7-10.4) |
615 | 10.6 (8.3-12.9) |
Antipsychotics | 7 | NA | 137 | 4.5 (3.3-5.6) |
340 | 5.2 (3.9-6.5) |
228 | 3.1 (2.2-4.0) |
176 | 1.9 (1.4-2.4) |
41 | 0.5 (0.3-0.6) |
13 | NA |
Diabetes agents | 10 | NA | 100 | 2.8 (1.8-3.8) |
499 | 7.3 (5.3-9.2) |
891 | 14.2 (11.3-17.2) |
1786 | 18.2 (14.8-21.7) |
1722 | 18.6 (14.9-22.4) |
839 | 15.2 (11.4-19.0) |
Dietary supplementse | 46 | 1.8 (0.8-2.8) |
55 | 2.0 (1.3-2.6) |
201 | 3.7 (3.0-4.4) |
174 | 2.9 (2.5-3.4) |
125 | 1.4 (1.0-1.7) |
72 | 1.0 (0.7-1.3) |
38 | 1.0 (0.6-1.3) |
Non-opioid-containing analgesics | 36 | 1.6 (0.9-2.4) |
49 | 1.7 (0.9-2.5) |
88 | 1.6 (1.1-2.0) |
68 | 1.1 (0.7-1.5) |
31 | 0.3 (0.1-0.5)d |
11 | NA | 5 | NA |
Nonsteroidal anti-inflammatory drugs | 52 | 2.8 (1.7-3.9) |
117 | 3.9 (2.8-5.0) |
225 | 4.0 (3.2-4.8) |
166 | 3.2 (2.6-3.7) |
132 | 1.5 (1.2-1.8) |
69 | 0.8 (0.5-1.0) |
18 | NA |
Opioid analgesics | 20 | 0.6 (0.1-1.0)d |
93 | 3.0 (2.2-3.8) |
422 | 7.8 (6.8-8.8) |
382 | 6.8 (5.7-7.9) |
536 | 6.9 (5.9-8.0) |
354 | 4.6 (3.9-5.4) |
151 | 3.5 (2.6-4.5) |
Sedative or hypnotic agents | 11 | NA | 55 | 2.0 (1.1-2.9) |
128 | 2.3 (1.4-3.1) |
160 | 2.8 (1.8-3.7) |
145 | 1.6 (1.2-2.1) |
106 | 1.4 (0.9-1.9) |
53 | 0.9 (0.5-1.3) |
Stimulants | 13 | NA | 116 | 3.8 (2.8-4.7) |
50 | 0.9 (0.5-1.3) |
18 | NA | 5 | NA | 4 | NA | 1 | NA |
Vaccines | 455 | 19.5 (16.2-22.8) |
111 | 3.7 (2.8-4.6) |
89 | 1.8 (1.3-2.4) |
89 | 1.6 (1.0-2.1) |
81 | 1.1 (0.8-1.3) |
64 | 0.8 (0.5-1.1) |
16 | NA |
All other drug classesf | 284 | 10.5 (8.2-12.7) |
860 | 26.8 (24.6-29.1) |
1454 | 26.3 (24.3-28.3) |
1522 | 26.3 (24.6-28.0) |
1986 | 23.2 (21.0-25.4) |
1328 | 16.9 (14.5-19.3) |
548 | 11.6 (9.0-14.1) |
>1 Drug class implicated | 51 | 1.7 (0.9-2.5) |
211 | 6.9 (5.7-8.1) |
425 | 7.5 (6.3-8.8) |
482 | 7.9 (7.0-8.8) |
691 | 7.8 (6.6-8.9) |
719 | 8.8 (7.1-10.6) |
509 | 9.5 (6.8-12.2) |
Abbreviation: NA, estimates based on fewer than 20 cases are considered statistically unreliable and are not shown.
Data are based on 42 585 cases from the National Electronic Injury Surveillance System–Cooperative Adverse Drug Event Surveillance project, US Centers for Disease Control and Prevention. Data exclude ED visits for abuse or self-harm. Data for specific drug classes represent only ED visits in which a single drug class was implicated. Patient age missing for 1 case.
Excludes ED visits for unsupervised medication ingestions by children aged 10 years or younger.
Calculated from statistical weighting of cases based on the sample design.
Coefficient of variation greater than 30%.
In addition to related products.
In which a single drug class was implicated.
Among older adults, the 15 most common drug products implicated were involved in an estimated 68.5% (95% CI, 64.5%-72.5%) of ED visits for adverse drug events (Table 4). Four of the 15 most common drug products implicated in ED visits for adverse drug events among older adults were anticoagulants (warfarin, rivaroxaban, dabigatran, and enoxaparin) and 5 were diabetes agents (insulin, metformin, glipizide, glyburide, and glimepiride). Anticoagulants alone were implicated in 27.5% (95% CI, 23.3%-31.7%) of ED visits for adverse drug events among adults aged 65 to 79 years and in 38.8% (95% CI, 33.7%-43.8%) of ED visits for adverse drug events among those aged 80 years or older (Table 4 and eFigure in the Supplement).
Warfarin was implicated in an estimated 85.7% (95% CI, 82.8%-88.6%) of ED visits for anticoagulant adverse drug events among older adults (aged ≥65 years) and target-specific oral anticoagulants (apixaban, dabigatran, and rivaroxaban) were implicated in an estimated 12.0% (95% CI, 8.9%-15.1%) of ED visits for anticoagulant adverse drug events. Among older adults, the hospitalization rate for ED visits for adverse drug events from target-specific oral anticoagulants (55.7%; 95% CI, 45.6%-65.9%) was similar to the rate for warfarin (49.8%; 95% CI, 42.9%-56.7%).
Three drug classes (anticoagulants, diabetes agents, and opioid analgesics) recently targeted by federal patient safety initiatives4 were implicated in an estimated 59.9% (95% CI, 56.8%-62.9%) of ED visits for adverse drug events among older adults (aged ≥65 years). Potentially inappropriate medications according to the Beers criteria were implicated in an estimated 3.4% (95% CI, 2.8%-4.0%) of ED visits for adverse drug events and potentially inappropriate medications to always avoid were implicated in 1.8% (95% CI, 1.5%-2.1%) of ED visits for adverse drug events.
The most commonly implicated drug classes were involved in clinically significant adverse events (Table 5). There was documented hemorrhage in an estimated 79.4% (95% CI, 75.2%-83.6%) of ED visits for adverse drug events involving anticoagulants alone; moderate to severe allergic reactions in an estimated 18.2% (95% CI, 15.4%-21.0%) of ED visits for adverse drug events involving antibiotics alone; hypoglycemia with moderate to severe neurological effects (eg, loss of consciousness or altered mental status) in an estimated 47.6% (95% CI, 39.4%-55.7%) of ED visits for adverse drug events involving diabetes agents alone; and moderate to severe neurological effects in an estimated 33.9% (95% CI, 29.1%-38.7%) of ED visits for adverse drug events involving opioid analgesics alone.
Table 5.
Adverse Event Manifestationb | ED Visits for ADEs | |
---|---|---|
No. of Cases | National Estimate, % (95% CI)c | |
Anticoagulants (n = 6290) | ||
Hemorrhage | 5101 | 79.4 (75.2-83.6) |
Central nervous systemd | 262 | 2.8 (1.4-4.2) |
Pulmonary | 149 | 2.3 (1.7-3.0) |
Gastrointestinal | 1577 | 27.0 (21.0-32.9) |
Genitourinary | 547 | 9.5 (6.6-12.4) |
Epistaxis | 815 | 15.0 (11.7-18.3) |
Skin, wound, or other minor | 1418 | 18.8 (13.2-24.4) |
Other hemorrhage types | 333 | 4.1 (2.5-5.6) |
Laboratory abnormality only (eg, elevated international normalized ratio) or unspecified overdose | 1116 | 19.5 (15.5-23.6) |
Other or unspecified effect | 73 | 1.1 (0.7-1.5) |
Antibiotics (n = 6017) | ||
Moderate to severe allergic reactione | 1107 | 18.2 (15.4-21.0) |
Neurological or psychiatric effect (eg, headache, anxiety) | 56 | 0.9 (0.6-1.2) |
Sensory or motor disturbance (eg, dizziness, syncope, muscular weakness) | 107 | 1.8 (1.3-2.3) |
Secondary infection (eg, candidiasis, Clostridium difficile colitis) | 41 | 0.8 (0.4-1.3) |
Gastrointestinal disturbance | 690 | 11.9 (8.4-15.4) |
Mild allergic reactionf | 3843 | 63.6 (59.7-67.5) |
Other or unspecified effect | 173 | 2.8 (2.2-3.3) |
Diabetes Agents (n = 5883) | ||
Hypoglycemia with moderate to severe effect | 2697 | 47.6 (39.4-55.7) |
Plus shock, loss of consciousness, or seizure | 844 | 15.6 (10.6-20.6) |
Plus fall or other injury (eg, road traffic accident) | 295 | 4.5 (3.1-6.0) |
Plus altered mental status or depressed level of consciousness | 1558 | 27.4 (20.8-34.1) |
Hypoglycemia with mild or unspecified effect | 2610 | 42.1 (34.8-49.5) |
Plus presyncope, syncope, or dizziness | 499 | 8.8 (6.2-11.3) |
Plus other neurological effect (eg, hyperhidrosis, tremor, dysarthria) | 315 | 5.0 (3.6-6.4) |
Plus other effect | 236 | 3.6 (2.6-4.5) |
Plus unspecified effect | 1560 | 24.8 (16.6-32.9) |
Other or unspecified effect | 576 | 10.3 (7.6-13.0) |
Opioid Analgesics (n = 2119)g | ||
Moderate to severe neurological effect | 736 | 33.9 (29.1-38.7) |
Loss of consciousness or respiratory distress (eg, respiratory depression, dyspnea, hypoxia) | 243 | 10.7 (8.2-13.3) |
Fall or other injury (eg, road traffic accident) | 80 | 3.8 (2.4-5.3) |
Altered mental status or depressed level of consciousness | 413 | 19.3 (15.6-23.1) |
Moderate to severe allergic reactione | 75 | 3.7 (2.4-5.0) |
Mild neurological effect | 345 | 16.3 (13.6-19.0) |
Presyncope, syncope, dizziness, muscular weakness, or gait or balance disturbance | 202 | 9.5 (7.2-11.7) |
Other neurological or psychiatric effect (eg, lethargy, fatigue, dysarthria) | 143 | 6.8 (4.9-8.7) |
Cardiovascular effect (eg, palpitations, hypotension) | 25 | 1.5 (0.8-2.2) |
Gastrointestinal or genitourinary disturbance | 433 | 21.4 (17.1-25.7) |
Mild allergic reactionf | 230 | 11.3 (8.9-13.6) |
Other or unspecified effect | 275 | 11.9 (8.9-15.0) |
Data are based on 42 585 cases from the National Electronic Injury Surveillance System–Cooperative Adverse Drug Event Surveillance project, US Centers for Disease Control and Prevention. Data represent only ED visits in which a single drug class was implicated (86.9% of estimated ED visits involving anticoagulants; 93.8% of estimated ED visits involving antibiotics; 98.4% of estimated ED visits involving diabetes agents; and 79.8% of estimated ED visits involving opioid analgesics).
Adverse event manifestations are mutually exclusive and were assigned hierarchically for all drug classes. For example, an ED visit in which a patient experienced both rectal bleeding and hematuria while on an anticoagulant would be categorized as gastrointestinal hemorrhage; an ED visit in which a patient experienced both hypoglycemic seizure and a fall while taking a diabetes agent would be categorized as hypoglycemia plus shock, loss of consciousness, or seizure.
Calculated from statistical weighting of cases based on the sample design.
Epidural or subdural hematoma, hemorrhagic stroke, and intracerebral or subarachnoid hemorrhage.
Anaphylaxis, angioedema, drug reaction with eosinophilia and systemic symptoms, erythema multiforme, exfoliative dermatitis, facial-pharyngeal-genital edema, hyperhidrosis or chills, hypersensitivity vasculitis, red man syndrome, allergy-related respiratory compromise (eg, bronchospasm, dyspnea, hyperventilation, tachypnea, throat tightness, wheezing), serum sickness, and Stevens-Johnson syndrome.
Dermatitis, drug eruption, erythema, flushing, localized or peripheral edema, pruritus, rash, and urticaria.
Excludes ED visits for abuse or self-harm.
Discussion
The most common drug classes implicated in ED visits for adverse drug events in the United States are the same ones identified a decade ago–anticoagulants, antibiotics, diabetes agents, and opioid analgesics.4 Even after accounting for prescribing frequency, the rate of ED visits for adverse drug events per prescription previously has been found to be significantly higher for anticoagulants and diabetes agents than for most other medications, including those that are currently considered high risk in nationally recognized health care quality measures.10 For antibiotics, per-prescription risk has been found to outweigh benefits for many outpatient upper respiratorytract infections.11,12 Targeting adverse drug events common among specific patient populations, such as among the youngest (aged ≤19 years) and oldest (aged ≥65 years), may help further focus outpatient medication safety efforts.
Outpatient antibiotic prescribing has declined during the past decade; however, prescribing rates remain highest for children13 and antibiotics continue to account for most ED visits for adverse drug events among young children.11 More than half of US antibiotic prescriptions for children aged 14 years or younger are for acute respiratory tract infections, which are commonly viral, or infections for which watchful waiting is recommended.14 Reducing inappropriate antibiotic use with interventions, such as clinical decision support and benchmarking of outpatient prescribing rates, may help to reduce the risk of medication harms and antimicrobial resistance.15
Antipsychotics were the second most commonly implicated drug class in ED visits for adverse drug events among older children and adolescents. The American Psychiatric Association currently warns against using antipsychotics as first-line therapy in children and adolescents for conditions other than psychotic disorders16; however, antipsychotic prescribing has increased sharply during the last 2 decades.17 Up to 75% of antipsychotic use in children and adolescents is estimated to be for off-label indications and there is evidence of low adherence to recommendations for safety monitoring.18,19 Quality reporting measures and revisions to payment policies have reduced unnecessary use of antipsychotic prescriptions among older adults (aged ≥65 years).20 Improving safe use of antipsychotics in children and adolescents may require similar strategies.
The proportion of ED visits for adverse drug events involving anticoagulants has increased during the last decade along with increased anticoagulant use. From 2009 to 2014, oral anticoagulant use increasedby approximately 38%,21 whereas the proportion of ED visits for anticoagulants increased by 57% (eTable 3 in the Supplement). The additional increase in ED visits for anticoagulant adverse drug events may be from improved case identification since 2006, when data abstractors received supplemental training after anticoagulant adverse drug events were found to be underidentified.22
Although not all anticoagulant-related bleeding is preventable, anticoagulant management services and patient self-testing and self-management programs have been shown to reduce adverse drug events from anticoagulants.23 However, most outpatients do not participate in these programs,24,25 and these strategies are not well incentivized under public and private payer safety policies for patients.26 A recent report from the US Department of Health and Human Services calls for enhanced adverse drug event prevention efforts for anticoagulants.26
New clinical performance improvement measures for systematic and coordinated outpatient management of anticoagulants have been introduced by the Centers for Medicare & Medicaid Services as part of the Merit-Based Incentive Payment System and will replace the sustainable growth rate formula payment structure for many physicians.27 It is unknown whether payment policies that incentivize practices and physicians to more optimally manage anticoagulant treatments will reduce the burden of adverse drug events; however, the recognition by a national quality payment program of the value of evidence-based anticoagulant management in improving the quality of care for older adults (aged ≥65 years) is an important step toward improving anticoagulant use.
Newly approved, target-specific oral anticoagulants are marketed as safer alternatives to warfarin; however, these agents are increasingly implicatedin ED visits for anticoagulant adverse drug events, particularly among older adults (aged ≥65 years). Rivaroxaban is now the fifth and dabigatran the tenth most commonly implicated drug in ED visits for adverse drug events among older adults. Although these drugs do not currently require routine laboratory monitoring, their optimal use is dependent on the adjustment of dosages for special populations, ensuring adherence because of short half-lives, monitoring drug interactions, and managing perioperative and reversal strategies.28 Anticoagulation management services intended for patients taking warfarin may now have a role in improving thromboembolic and hemorrhagic outcomes for new oral agents as well.28
The Beers criteria include lists of potentially inappropriate medications such as first-generation antihistamines, skeletalmuscle relaxants, and short- and intermediate-acting benzodiazepines that should always be avoided in most older adults (aged ≥65 years) owing to the availability of safer or more effective alternatives.3 The Beers criteria also include potentially inappropriate medications to be avoided under certain circumstances, such as long-term use of nonsteroidal anti-inflammatory drugs and proton-pump inhibitors.3 Among older adults, potentially inappropriate medications to always avoid according to the most updated Beers criteria were implicated in only 1.8% of estimated ED visits for adverse drug events and all potentially inappropriate medications were implicated in 3.4% of estimated ED visits for adverse drug events in 2013-2014. These findings are similar to the proportions of US ED visits for adverse drug events from potentially inappropriate medications identified in 2004-2005.10
The prevalence of potentially inappropriate medication use in older adults (aged ≥65 years) remains high,29 suggesting that the Beers criteria have limited utility in identifying patient populations who are at highest risk for adverse drug events. Despite the Beers criteria being primarily intended for practicing clinicians as a useful tool to guide clinical decision making for an individual patient,3 the criteria have become one of the primary methods for assessment of patient safety in older adults used by public and private payers,7,8 supplanting other interventions that may have a larger effect on outpatient medication safety. For example, diabetes agents were implicated in 1 of 8 ED visits for adverse drug events overall and in 1 of 5 ED visits for adverse drug events among older adults. Recent diabetes treatment guidelines recommend increasing glycemic thresholds for older patients at risk for hypoglycemia, particularly those with certain comorbidities or limited life expectancy, and residing in long-term care facilities.30-32
There are a number of study limitations that likely lead to underestimation of outpatient adverse drug events. First, this study includes only adverse drug events diagnosed and treated in EDs; patients directly admitted or treated in other settings (eg, physician offices) are not included. Second, ED physicians are less likely to identify low-severity or insidious adverse drug events, those that do not contribute to the patient’s “chief complaint,” and those that require extensive evaluation to diagnose.33,34 Third, fatal adverse drug events are not included because ED documentation practices vary for recording deaths. Fourth, estimates do not include visits related to pharmaceutical abuse or self-harm attempts.
The rapid increase in mortality from opioid analgesics in the United States has been well documented35; however, updated national morbidity data on pharmaceutical abuse are limited. Future inclusion of ED visits from abuse or self-harm of pharmaceutical products in the NEISS-CADES project is planned. Fifth, per-prescription rates of ED visits for adverse drug events, which can more accurately identify the direction of trends, were not calculated. Sixth, the NEISS-CADES project data are based on a sample of US hospital EDs and not a census; therefore, estimates are subject to sampling errors.
Direct comparison with previously published estimates of adverse drug events from other sources is challenging. Anti-coagulants, diabetes agents, and opioid analgesics also have been identified as the most common causes of medication-related harm in both inpatient and long-term care settings.26 Studies using International Classification of Diseases (ICD) codes to identify ED visits for adverse drug events have found lower estimates during previous years,36 but ICD codes have low sensitivity for identifying adverse drug events.37 Other nationally representative diagnostic code-based studies have identified additional drug classes (eg, corticosteroids) to be common causes of adverse drug events; however, without supporting clinical data, it is uncertain if these ED visits represent drug-induced harm or another drug-related problem, such as nonadherence or inadequate treatment.38
Some studies using pharmacist case review to identify adverse drug events resulting in ED visits have found additional events and drugs that ED physicians did not document. However, these studies used a broader outcome of medication-related “problems” that included nonadherence, therapeutic failures, and lack of therapy.33,39 Failing to prescribe or take a drug limits effectiveness, but is not an adverse drug event (harm caused by the use of a drug).40 Distinguishing conditions due to the absence of therapy from those due to drug-induced effects is necessary to implement appropriate interventions. Improving recognition of adverse drug events by ED physicians is certainly important, but in the interim there is ample opportunity to improve patient safety by focusing attention on the adverse drug events consistently found to be common, serious, and measurable. Targeting adverse drug events due to anticoagulants and diabetes agents in the inpatient setting has contributed to reductions in health care-related harm in US hospitals.41,42 Achieving measurable reductions in outpatient adverse drug events may also require focusing on the most common drugs implicated and the highest risk patients.
Conclusions
The prevalence of emergency department visits for adverse drug events in the United States was estimated to be 4 per 1000 individuals in 2013 and 2014. The most common drug classes implicated were anticoagulants, antibiotics, diabetes agents, and opioid analgesics.
Supplementary Material
Key Points.
Question What are the characteristics of adverse drug events that lead to US emergency department (ED) visits?
Findings Based on 2013-2014 nationally representative surveillance data, an estimated 4 ED visits for adverse drug events occurred per 1000 individuals annually Among children (aged ≤5 years), antibiotics were most commonly implicated; among older children and adolescents (aged 6-19 years), antibiotics were most commonly implicated, followed by antipsychotics; and among older adults (aged ≥65 years), anticoagulants, diabetes agents, and opioid analgesics were implicated in approximately 60% of ED visits for adverse drug events.
Meaning Adverse drug events from anticoagulants, antibiotics, diabetes agents, opioid analgesics, and antipsychotics are a common reason for ED visits and may benefit from patient safety initiatives.
Acknowledgments
Funding/Support: This study was funded by the US federal government.
Footnotes
Conflict of Interest Disclosures: The authors have completed and submitted the ICMJE Form for Disclosure of Potential Conflicts of Interest and none were reported.
Role of the Funder/Sponsor: Federal government employees had a role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.
Disclaimer: The findings and conclusions in this study are those of the authors and do not necessarily represent the official position of the US Centers for Disease Control and Prevention (CDC).
Contributor Information
Nadine Shehab, Division of Healthcare Quality Promotion, US Centers for Disease Control and Prevention, Atlanta, Georgia.
Maribeth C. Lovegrove, Division of Healthcare Quality Promotion, US Centers for Disease Control and Prevention, Atlanta, Georgia.
Andrew I. Geller, Division of Healthcare Quality Promotion, US Centers for Disease Control and Prevention, Atlanta, Georgia.
Kathleen O. Rose, Northrup Grumman Corporation, Atlanta, Georgia.
Nina J. Weidle, Chenega Government Consulting, Atlanta, Georgia.
Daniel S. Budnitz, Division of Healthcare Quality Promotion, US Centers for Disease Control and Prevention, Atlanta, Georgia.
REFERENCES
- 1.Schumock GT, Li EC, Suda KJ, et al. National trends in prescription drug expenditures and projections for 2015. Am J Health Syst Pharm. 2015; 72(9):717–736. [DOI] [PubMed] [Google Scholar]
- 2.Institute of Medicine. Preventing Medication Errors. Washington, DC: National Academies Press; 2006. [Google Scholar]
- 3.American Geriatrics Society. American Geriatrics Society 2015 updated Beers criteria for potentially inappropriate medication use in older adults. J Am Geriatr Soc. 2015;63(11):2227–2246. [DOI] [PubMed] [Google Scholar]
- 4.Budnitz DS, Pollock DA, Weidenbach KN, et al. National surveillance of emergency department visits for outpatient adverse drug events. JAMA. 2006;296(15):1858–1866. [DOI] [PubMed] [Google Scholar]
- 5.Schroeder T, Ault K. NEISS all injury program. http://www.icpsr.umich.edu/cgi-bin/file?comp=none&study=36280&ds=1&file_id=1194767&path=ICPSR. Accessed August 16, 2016.
- 6.US Centers for Disease Control and Prevention. Distinguishing public health research and public health nonresearch. http://www.cdc.gov/od/science/integrity/docs/cdc-policy-distinguishing-public-health-research-nonresearch.pdf. Accessed August 16, 2016.
- 7.National Committee for Quality Assurance. HEDIS measures 2015. http://www.ncqa.org/HEDISQualityMeasurement/HEDISMeasures/HEDIS2015/HEDIS2015NDCLicense/HEDIS2015FinalNDCLists.aspx. Accessed August 16, 2016.
- 8.Centers for Medicare & Medicaid Services. Physician Quality Reporting System: measure #238 (NQF 0022). https://pqrs.cms.gov/download/c2h5-33fn/application/pdf. Accessed August 16, 2016.
- 9.US Centers for Disease Control and Prevention. Bridged-race population estimates: 1990-2014. https://wonder.cdc.gov/bridged-race-population.html. Accessed August 16, 2016.
- 10.Budnitz DS, Shehab N, Kegler SR, Richards CL. Medication use leading to emergency department visits for adverse drug events in older adults. Ann Intern Med. 2007;147(11):755–765. [DOI] [PubMed] [Google Scholar]
- 11.Shehab N, Patel PR, Srinivasan A, Budnitz DS. Emergency department visits for antibiotic-associated adverse events. Clin Infect Dis. 2008;47(6):735–743. [DOI] [PubMed] [Google Scholar]
- 12.Linder JA.Antibiotics for treatment of acute respiratory tract infections. Clin Infect Dis. 2008;47(6):744–746. [DOI] [PubMed] [Google Scholar]
- 13.Frenk SM, Kit BK, Lukacs SL, et al. Trends in the use of prescription antibiotics. J Antimicrob Chemother. 2016;71(1):251–256. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 14.US Centers for Disease Control and Prevention. Office-related antibiotic prescribing for persons aged ≤14 years—United States, 1993-1994 to 2007-2008. JAMA. 2011;306(13):1432–1434. [Google Scholar]
- 15.US Centers for Disease Control and Prevention. Get smart: know when antibiotics work. http://www.cdc.gov/getsmart/community/improving-prescribing/interventions/index.html. Accessed August 16, 2016.
- 16.American Board of Internal Medicine Foundation. Antipsychotics in children and adolescents. http://www.choosingwisely.org/clinician-lists/american-psychiatric-association-antipsychotics-in-children-or-adolescents/. Accessed August 16, 2016.
- 17.Olfson M, Blanco C, Liu SM, et al. National trends in the office-based treatment of children, adolescents, and adults with antipsychotics. Arch Gen Psychiatry. 2012;69(12):1247–1256. [DOI] [PubMed] [Google Scholar]
- 18.Carton L, Cottencin O, Lapeyre-Mestre M, et al. Off-label prescribing of antipsychotics in adults, children and elderly individuals. Curr Pharm Des. 2015;21(23):3280–329. [DOI] [PubMed] [Google Scholar]
- 19.Rettew DC, Greenblatt J, Kamon J, et al. Antipsychotic medication prescribing in children enrolled in Medicaid. Pediatrics. 2015;135(4):658–665. [DOI] [PubMed] [Google Scholar]
- 20.Centers for Medicare & Medicaid Services. Data show national partnership to improve dementia care exceeds goals to reduce unnecessary antipsychotic medications in nursing homes. https://www.cms.gov/newsroom/MediareleaseDatabase/Fact-sheets/2014-Fact-sheets-items/2014-09-19.html. Accessed August 16, 2016.
- 21.Barnes GD, Lucas E, Alexander GC, Goldberger ZD. National trends in ambulatory oral anticoagulant use. Am J Med. 2015;128(12):1300–5.e2. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 22.US Centers for Disease Control and Prevention. Assessing the National Electronic Injury Surveillance System-Cooperative Adverse Drug Event Surveillance project. MMWR Morb Mortal Wkly Rep. 2005;54(15):380–383. [PubMed] [Google Scholar]
- 23.Holbrook A, Schulman S, Witt DM, et al. Evidence-based management of anticoagulant therapy. Chest. 2012;141(2)(suppl):e152S–e184S. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 24.Nutescu EA. Anticoagulation management services. Pharmacotherapy. 2010;30(4):327–329. [DOI] [PubMed] [Google Scholar]
- 25.Nutescu EA, Bathija S, Sharp LK, et al. Anticoagulation patient self-monitoring in the United States. Pharmacotherapy. 2011;31(12):1161–1174. [DOI] [PubMed] [Google Scholar]
- 26.US Department of Health and Human Services. National action plan for adverse drug event prevention. https://health.gov/hcq/ade.asp. Accessed August 16, 2016.
- 27.Centers for Medicare & Medicaid Services. Merit-based incentive payment system and alternative payment model incentive under the physician fee schedule, and criteria for physician-focused payment models. https://www.gpo.gov/fdsys/pkg/FR-2016-05-09/pdf/2016-10032.pdf. Accessed August 16, 2016.
- 28.Barnes GD, Nallamothu BK, Sales AE, Froehlich JB. Reimagining anticoagulation clinics in the era of direct oral anticoagulants. Circ Cardiovasc Qual Outcomes. 2016;9(2):182–185. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 29.Jirón M, Pate V, Hanson LC, et al. Trends in prevalence and determinants of potentially inappropriate prescribing in the United States. J Am Geriatr Soc. 2016;64(4):788–79. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 30.American Diabetes Association. 10: Older adults. Diabetes Care. 2016;39(suppl 1):S81–S85. [DOI] [PubMed] [Google Scholar]
- 31.Munshi MN, Florez H, Huang ES, et al. Management of diabetes in long-term care and skilled nursing facilities. Diabetes Care. 2016;39(2): 308–318. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 32.Lipska KJ, Krumholz H, Soones T, Lee SJ. Polypharmacy in the aging patient. JAMA. 2016;315(10):1034–1045. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 33.Hohl CM, Robitaille C, Lord V, et al. Emergency physician recognition of adverse drug-related events in elder patients presenting to an emergency department. Acad Emerg Med. 2005;12(3):197–205. [DOI] [PubMed] [Google Scholar]
- 34.Roulet L, Ballereau F, Hardouin JB, et al. Adverse drug event nonrecognition in emergency departments. J Emerg Med. 2014;46(6):857–864. [DOI] [PubMed] [Google Scholar]
- 35.Rudd RA, Aleshire N, Zibbell JE, Gladden RM. Increases in drug and opioid overdose deaths. MMWR Morb Mortal Wkly Rep. 2016;64(50–51): 1378–1382. [DOI] [PubMed] [Google Scholar]
- 36.Albert M, McCaig LF, Uddin S. Emergency department visits for drug poisoning. NCHS Data Brief. 2015;196(196):1–8. [PubMed] [Google Scholar]
- 37.Leonard CE, Haynes K, Localio AR, et al. Diagnostic E-codes for commonly used, narrow therapeutic index medications poorly predict adverse drug events. J Clin Epidemiol. 2008;61(6):561–571. [DOI] [PubMed] [Google Scholar]
- 38.Lucado J, Paez K, Elixhauser A. Medication-related adverse outcomes in US hospitals and emergency departments. http://www.hcup-us.ahrq.gov/reports/statbriefs/sb109.pdf. Accessed August 16, 2016. [PubMed]
- 39.Hohl CM, Zed PJ, Brubacher JR, et al. Do emergency physicians attribute drug-related emergency department visits to medication-related problems? Ann Emerg Med. 2010;55(6):493–502.e4. [DOI] [PubMed] [Google Scholar]
- 40.Nebeker JR, Barach P, Samore MH. Clarifying adverse drug events. Ann Intern Med. 2004;140(10):795–801. [DOI] [PubMed] [Google Scholar]
- 41.Agency for Healthcare Research and Quality. Interim data from national efforts to make care safer, 2010-2014. http://www.ahrq.gov/professionals/quality-patient-safety/pfp/interimhacrate2014.html. Accessed August 16, 2016.
- 42.Agency for Healthcare Research and Quality. Methods to estimate the baseline 2010 PFP national hospital-acquired condition rate. http://www.ahrq.gov/professionals/quality-patient-safety/pfp/index.html#methods. Accessed August 16, 2016.
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