Osama M. Ahmed

This Personal View is about our experience with preclinical education as medical students. We discuss the problem with current medical education in light of an ever-growing body of medical knowledge and increasing student disengagement with preclinical lectures. We briefly review the concept of retrieval practice as an effective, evidence-based learning strategy that helped us retain knowledge for longer periods and propose that medical educators should adopt this strategy to best prepare medical students to navigate the vastly expanding scope of modern medicine.

Purpose: We performed an epidemiological study of orbital lymphoma in the United States to determine how histological subtypes confer differing prognosis, and understand other factors associated with survival. Methods: All patients in the Surveillance, Epidemiology and End Results database diagnosed with a histologically confirmed orbital lymphoma between 1973 and 2014 were included. Exclusion criteria included diagnosis at autopsy and the presence of other malignancies. Measures included patient demographic information, histological subtype and treatment modalities. Outcomes included overall and disease specific survival. Results: Of the 1504 cases identified, 702 were male (46.7%, mean age: 64.4 years, standard deviation [SD]: 15.3) and 802 were female (53.3%, mean age: 67.5 years, SD: 14.3). Mucosal associated lymphoid tissue (MALT) (49.5%) and diffuse large B cell lymphoma (DLBCL) (19.5%) were the two most common histologic subtypes. MALT lymphoma conferred the best prognosis (10-year cancer specific survival [CSS] 90.2%, 95% Confidence Interval [CI] 87.4% – 93.1%) and DLBCL conferred the worst prognosis (10-year CSS 68.6%, 95% CI 62.5% – 75.3%) (p < .001, log-rank test). Older age (Hazard Ratio [HR]: 3.71, 95% Confidence Interval [CI]: 2.94–4.66, p < .001), male sex (HR: 1.22, 95% CI: 1.039–1.441, p = .015), no radiation (HR: 1.72, 95% CI: 1.46–2.02, p < .001) and DLBCL histology were significant predictors of worse overall survival. Conclusions: DLBCL histology confers the worst outcomes whereas MALT lymphoma confers the best outcome in orbital lymphoma. Age, gender, and radiation treatment also influence survival. These epidemiological results can be used clinically to communicate outcomes on the basis of patient characteristics and disease histology.

Background: Deploying accurate computable phenotypes in pragmatic trials requires a trade-off between precise and clinically sensical variable selection. In particular, evaluating the medical encounter to assess a pattern leading to clinically significant impairment or distress indicative of disease is a difficult modeling challenge for the emergency department. Objective: This study aimed to derive and validate an electronic health record–based computable phenotype to identify emergency department patients with opioid use disorder using physician chart review as a reference standard. Methods: A two-algorithm computable phenotype was developed and evaluated using structured clinical data across 13 emergency departments in two large health care systems. Algorithm 1 combined clinician and billing codes. Algorithm 2 used chief complaint structured data suggestive of opioid use disorder. To evaluate the algorithms in both internal and external validation phases, two emergency medicine physicians, with a third acting as adjudicator, reviewed a pragmatic sample of 231 charts: 125 internal validation (75 positive and 50 negative), 106 external validation (56 positive and 50 negative). Results: Cohen kappa, measuring agreement between reviewers, for the internal and external validation cohorts was 0.95 and 0.93, respectively. In the internal validation phase, Algorithm 1 had a positive predictive value (PPV) of 0.96 (95% CI 0.863-0.995) and a negative predictive value (NPV) of 0.98 (95% CI 0.893-0.999), and Algorithm 2 had a PPV of 0.8 (95% CI 0.593-0.932) and an NPV of 1.0 (one-sided 97.5% CI 0.863-1). In the external validation phase, the phenotype had a PPV of 0.95 (95% CI 0.851-0.989) and an NPV of 0.92 (95% CI 0.807-0.978). Conclusions: This phenotype detected emergency department patients with opioid use disorder with high predictive values and reliability. Its algorithms were transportable across health care systems and have potential value for both clinical and research purposes.

Journal of Medical Internet Research - International Scientific Journal for Medical Research, Information and Communication on the Internet #Preprint #PeerReviewMe: Warning: This is a unreviewed preprint. Readers are warned that the document has not been peer-reviewed by expert/patient reviewers or an academic editor, may contain misleading claims, and is likely to undergo changes before final publication, if accepted, or may have been rejected/withdrawn. Readers with interest and expertise are encouraged to sign up as peer-reviewer, if the paper is within an open peer-review period. Please cite this preprint only for review purposes or for grant applications and CVs (if you are the author). Background: Emergency Departments (EDs) frequently care for individuals with Opioid Use Disorder (OUD). Buprenorphine (BUP) is an effective treatment option for patients with OUD that can safely be initiated in the ED. At present, BUP is rarely initiated as a part of routine ED care. Clinical decision support (CDS) could accelerate adoption of ED-initiated BUP into routine emergency care. Objective: To design and formatively evaluate a user-centered decision support tool for ED initiation of buprenorphine for patients with OUD. Methods: User-centered design with iterative prototype development was used. Initial observations and interviews identified workflows and information needs. The design team and key stakeholders reviewed prototype designs to ensure accuracy. Five prototypes were evaluated and iteratively refined informed by feedback from 26 attending and resident physicians until thematic saturation was reached. Results: Early feedback identified concerns with the initial CDS design: an alert with several screens. The timing of the alert led to quick dismissal without using the tool. User feedback on subsequent iterations informed the development of a flexible tool to support clinicians with varied levels experience with the intervention by providing both one-click options for direct activation of care pathways as well as user-activated support for critical decision points. The final design resolved challenging navigation issues through targeted placement, color, and design of the decision support modules and care pathways. In final testing, users expressed that the tool could be easily learned without training and was reasonable for use during routine emergency care. Conclusions: A user-centered design process helped designers to better understand users’ needs for a web-based clinical decision tool to support ED initiation of buprenorphine for OUD. The process identified varying needs across user experience and familiarity with the protocol, leading to a flexible design supporting both direct care pathways and user-initiated decision support. Clinical Trial: N/A for design,

BACKGROUND Emergency departments (EDs) frequently care for individuals with opioid use disorder (OUD). Buprenorphine (BUP) is an effective treatment option for patients with OUD that can safely be initiated in the ED. At present, BUP is rarely initiated as a part of routine ED care. Clinical decision support (CDS) could accelerate adoption of ED-initiated BUP into routine emergency care. OBJECTIVE This study aimed to design and formatively evaluate a user-centered decision support tool for ED initiation of BUP for patients with OUD. METHODS User-centered design with iterative prototype development was used. Initial observations and interviews identified workflows and information needs. The design team and key stakeholders reviewed prototype designs to ensure accuracy. A total of 5 prototypes were evaluated and iteratively refined based on input from 26 attending and resident physicians. RESULTS Early feedback identified concerns with the initial CDS design: an alert with several screens. The timing of the alert led to quick dismissal without using the tool. User feedback on subsequent iterations informed the development of a flexible tool to support clinicians with varied levels of experience with the intervention by providing both one-click options for direct activation of care pathways and user-activated support for critical decision points. The final design resolved challenging navigation issues through targeted placement, color, and design of the decision support modules and care pathways. In final testing, users expressed that the tool could be easily learned without training and was reasonable for use during routine emergency care. CONCLUSIONS A user-centered design process helped designers to better understand users’ needs for a Web-based clinical decision tool to support ED initiation of BUP for OUD. The process identified varying needs across user experience and familiarity with the protocol, leading to a flexible design supporting both direct care pathways and user-initiated decision support.