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Medication error is an important cause of patient morbidity and mortality, yet it can be a confusing and underappreciated concept. This article provides a review for practicing physicians that focuses on medication error (1) terminology and definitions, (2) incidence, (3) risk factors, (4) avoidance strategies, and (5) disclosure and legal consequences. A medication error is any error that occurs at any point in the medication use process. It has been estimated by the Institute of Medicine that medication errors cause 1 of 131 outpatient and 1 of 854 inpatient deaths. Medication factors (eg, similar sounding names, low therapeutic index), patient factors (eg, poor renal or hepatic function, impaired cognition, polypharmacy), and health care professional factors (eg, use of abbreviations in prescriptions and other communications, cognitive biases) can precipitate medication errors. Consequences faced by physicians after medication errors can include loss of patient trust, civil actions, criminal charges, and medical board discipline. Methods to prevent medication errors from occurring (eg, use of information technology, better drug labeling, and medication reconciliation) have been used with varying success. When an error is discovered, patients expect disclosure that is timely, given in person, and accompanied with an apology and communication of efforts to prevent future errors. Learning more about medication errors may enhance health care professionals' ability to provide safe care to their patients.

The term off-label drug use (OLDU) is used extensively in the medical literature, continuing medical education exercises, and the media. Yet, we propose that many health care professionals have an underappreciation of its definition, prevalence, and implications. This article introduces and answers 10 questions regarding OLDU in an effort to clarify the practice's meaning, breadth of application, acceptance, and liabilities. Off-label drug use involves prescribing medications for indications, or using a dosage or dosage form, that have not been approved by the US Food and Drug Administration. Since the Food and Drug Administration does not regulate the practice of medicine, OLDU has become common. It occurs in every specialty of medicine, but it may be more common in areas of medicine in which the patient population is less likely to be included in clinical trials (eg, pediatric, pregnant, or psychiatric patients). Pharmaceutical companies are not allowed to promote their medications for an off-label use, which has lead to several large settlements for illegal marketing. To limit liability, physicians should prescribe medications only for indications that they believe are in the best interest of the patient. In addition, health care professionals should educate themselves about OLDU to weigh the risks and benefits and provide the best possible care for their patients.

Background The U.S. News & World Report has used the Doximity social networking site to determine rankings for 27 medical specialties, which influence medical students' choices. Despite concerns about the validity of these rankings, few studies have explored whether Doximity rankings correlate with program characteristics. We aim to determine associations between Doximity internal medicine reputation rank and publicly available program characteristics. Methods We performed a cross-sectional study of the 566 internal medicine residencies with a Doximity reputation rank from 2020. Doximity rankings were linked with publicly available sources, including the American Medical Association’s FREIDA, the American Board of Internal Medicine, the Accreditation Council for Graduate Medical Education, the Centers for Medicare and Medicaid Services Quality System, and U.S. News Best Hospitals Ranking. Variables included resident demographics, faculty characteristics, and program features. Statistical analyses involved univariable and multivariable linear regression. Results In multivariable analysis (parameter estimate ± standard error), higher ABIM pass rates (-1.30 ± 0.41), higher physician faculty-to-resident ratios (-14.10 ± 4.45), older programs (-1.07 ± 0.25), availability of research rotations (-38.56 ± 16.23), and larger program sizes (-1.09 ± 0.16) were associated with better Doximity ranks. Conversely, a higher percentage of international medical graduates (1.07 ± 0.19) and Doctors of Osteopathy (1.12 ± 0.27) were linked to lower rankings. Variables had an adjusted R2 of 0.53. Conclusions Doximity rankings were positively associated with publicly available characteristics of residency programs including higher ABIM pass rates, lower physician faculty-to-resident ratio, older program age, availability of a research rotation, and larger program size. Doximity rankings were negatively associated with a higher percentage of IMG and DO residents. These findings suggest that while Doximity rankings may be influenced by larger program sizes and higher self-reporting rates, they may also reflect meaningful indicators of program quality. The findings highlight the importance of research productivity and faculty ratios in enhancing program reputation and underscore potential disadvantages for community-based programs.

Background Continuing medical education (CME) often uses passive educational models including lectures. However, numerous studies have questioned the effectiveness of these less engaging educational strategies. Studies outside of CME suggest that engaged learning is associated with improved educational outcomes. However, measuring participants’ engagement can be challenging. We developed and determined the validity evidence for a novel instrument to assess learner engagement in CME. Methods We conducted a cross-sectional validation study at a large, didactic-style CME conference. Content validity evidence was established through review of literature and previously published engagement scales and conceptual frameworks on engagement, along with an iterative process involving experts in the field, to develop an eight-item Learner Engagement Instrument (LEI). Response process validity was established by vetting LEI items on item clarity and perceived meaning prior to implementation, as well as using a well-developed online platform with clear instructions. Internal structure validity evidence was based on factor analysis and calculating internal consistency reliability. Relations to other variables validity evidence was determined by examining associations between LEI and previously validated CME Teaching Effectiveness (CMETE) instrument scores. Following each presentation, all participants were invited to complete the LEI and the CMETE. Results 51 out of 206 participants completed the LEI and CMETE (response rate 25%) Correlations between the LEI and the CMETE overall scores were strong (r = 0.80). Internal consistency reliability for the LEI was excellent (Cronbach’s alpha = 0.96). To support validity to internal structure, a factor analysis was performed and revealed a two dimensional instrument consisting of internal and external engagement domains. The internal consistency reliabilities were 0.96 for the internal engagement domain and 0.95 for the external engagement domain. Conclusion Engagement, as measured by the LEI, is strongly related to teaching effectiveness. The LEI is supported by robust validity evidence including content, response process, internal structure, and relations to other variables. Given the relationship between learner engagement and teaching effectiveness, identifying more engaging and interactive methods for teaching in CME is recommended.

Background E-learning—the use of Internet technologies to enhance knowledge and performance—has become a widely accepted instructional approach. Little is known about the current use of e-learning in postgraduate medical education. To determine utilization of e-learning by United States internal medicine residency programs, program director (PD) perceptions of e-learning, and associations between e-learning use and residency program characteristics. Methods We conducted a national survey in collaboration with the Association of Program Directors in Internal Medicine of all United States internal medicine residency programs. Results Of the 368 PDs, 214 (58.2%) completed the e-learning survey. Use of synchronous e-learning at least sometimes, somewhat often, or very often was reported by 85 (39.7%); 153 programs (71.5%) use asynchronous e-learning at least sometimes, somewhat often, or very often. Most programs (168; 79%) do not have a budget to integrate e-learning. Mean (SD) scores for the PD perceptions of e-learning ranged from 3.01 (0.94) to 3.86 (0.72) on a 5-point scale. The odds of synchronous e-learning use were higher in programs with a budget for its implementation (odds ratio, 3.0 [95% CI, 1.04–8.7]; P  = .04). Conclusions Residency programs could be better resourced to integrate e-learning technologies. Asynchronous e-learning was used more than synchronous, which may be to accommodate busy resident schedules and duty-hour restrictions. PD perceptions of e-learning are relatively moderate and future research should determine whether PD reluctance to adopt e-learning is based on unawareness of the evidence, perceptions that e-learning is expensive, or judgments about value versus effectiveness.

To determine continuing medical education (CME) course participants' use of social media (SM) and their attitudes about the value of SM for enhancing CME education and to examine associations between participants' characteristics and attitudes toward SM. We conducted a cross-sectional survey and validation study of 539 participants at a Mayo Clinic Internal Medicine CME course in November 2011. The Social Media Use and Perception Instrument (SMUPI) consisted of 10 items (5-point Likert scales) and categorical response options. The main outcome measures were psychometric characteristics of the SMUPI scale, course participants' use of SM, and their attitudes regarding the importance of SM for enhancing CME. Of 539 CME course participants, 327 (61%) responded to the SMUPI survey. Most respondents (291 [89%]) reported using SM, with the most common types being YouTube (189 of the 327 participants [58%]) and Facebook (163 of 327 [50%]). Factor analysis revealed a 2-dimensional assessment of course participants' attitudes. Internal consistency reliability (Cronbach α) was excellent for factor 1 (0.94), factor 2 (0.89), and overall (0.94). The CME course participants' favorable attitudes toward SM were associated with younger age (20-29 years, mean score 3.13; 30-39 years, 3.40; 40-49 years, 3.39; 50-59 years, 3.18; 60-69 years, 2.93; and ≥70 years, 2.92; P=.02), using SM frequently (never, mean score 2.49; less than once monthly, 2.75; once monthly, 3.21; weekly, 3.31; and daily, 3.81; P<.0001), and professional degree (PhD, mean score 3.00; MD, 3.05; DO, 3.35; PA, 3.42; and NP, 3.50; P=.01). We describe the first validated measure of CME course participants' use of and attitudes toward SM. Our results suggest that CME course directors should guide SM strategies toward more youthful, technology-savvy CME participants and that SM will become increasingly worthwhile in CME as younger learners continue to enter the profession.

Most research on how to enhance response rates in physician surveys has been done using paper surveys. Uncertainties remain regarding how to enhance response rates in Internet-based surveys. To evaluate the impact of a low-cost nonmonetary incentive and paper mail reminders (formal letter and postcard) on response rates in Internet-based physician surveys. We executed a factorial-design randomized experiment while conducting a nationally representative Internet-based physician survey. We invited 3966 physicians (randomly selected from a commercial database of all licensed US physicians) via email to complete an Internet-based survey. We used 2 randomly assigned email messages: one message offered a book upon survey completion, whereas the other did not mention the book but was otherwise identical. All nonrespondents received several email reminders. Some physicians were further assigned at random to receive 1 reminder via paper mail (either a postcard or a letter) or no paper reminder. The primary outcome of this study was the survey response rate. Of the 3966 physicians who were invited, 451 (11.4%) responded to at least one survey question and 336 (8.5%) completed the entire survey. Of those who were offered a book, 345/2973 (11.6%) responded compared with 106/993 (10.7%) who were not offered a book (odds ratio 1.10, 95% CI 0.87-1.38, P=.42). Regarding the paper mail reminder, 168/1572 (10.7%) letter recipients, 148/1561 (9.5%) postcard recipients, and 69/767 (9.0%) email-only recipients responded (P=.35). The response rate for those receiving letters or postcards was similar (odds ratio 1.14, 95% CI 0.91-1.44, P=.26). Offering a modest nonmonetary incentive and sending a paper reminder did not improve survey response rate. Further research on how to enhance response rates in Internet-based physician surveys is needed.