Background: Teaching residents how to teach is a critical part of residents’ training in graduate medical education (GME). The purpose of this study was to assess the change in resident-as-teacher (RaT) instruction in GME over the past 15 years in the US. Methods: We used a quantitative and qualitative survey of all program directors (PDs) across specialties. We compared our findings with a previous work from 2000–2001 that studied the same matter. Finally, we qualitatively analyzed PDs’ responses regarding the reasons for implementing and not implementing RaT instruction. Results: Two hundred and twenty-one PDs completed the survey, which yields a response rate of 12.6%. Over 80% of PDs implement RaT, an increase of 26.34% compared to 2000–2001. RaT instruction uses multiple methods with didactic lectures reported as the most common, followed by role playing in simulated environments, then observing and giving feedback. Residents giving feedback, clinical supervision, and bedside teaching were the top three targeted skills. Through our qualitative analysis we identified five main reasons for implementing RaT: teaching is part of the residents’ role; learners desire formal RaT training; regulatory bodies require RaT training; RaT improves residents’ education; and RaT prepares residents for their current and future roles. Conclusion: The use of RaT instruction has increased significantly in GME. More and more PDs are realizing its importance in the residents’ formative training experience. Future studies should examine the effectiveness of each method for RaT instruction.

The overarching purpose of this study is to examine the current trends in interprofessional education (IPE) within graduate medical education in the Unites States. A survey was sent to program directors across with different specialties between March and April 2016. The survey was completed by 233 out of 1757 program directors, which represents a response rate of 13.3%. IPE is currently being used by over 60% of the GME program directors that completed the survey. The median number of IPE hours is 60. Classroom learning (70.8%) and team-based approaches (70.1%) to patient care are the two most common forms of IPE. The two most prevalent reasons for implementing IPE are improving collaboration (92.2%) and communication (87%). More than half of the program directors agreed or strongly agreed that lack of time both for teachers (54.4) and for residents (51.5%) are barriers to IPE. About one third of the respondents whose programs do not include IPE are interested in implementing some IPE in the future. IPE in its varying formats has been implemented as a training model by many residency programs. Further studies are needed to explore the comparative effectiveness of the different modalities of IPE.

Prescription opioids have been linked to over half of the 28,000 opioid overdose deaths in 2014. High rates of prescription opioid non-medical use have continued despite nearly all states implementing large-scale prescription drug monitoring programs (PDMP), which points to the need to examine the impact of state PDMP’s on curbing inappropriate opioid prescribing. In the short-term, PDMPs have been associated with short-term prescribing declines. Yet little is known about how such policies differentially impact patient subgroups or are interpreted by prescribing providers. Our objective was to compare volumes of prescribed opioids before and after Indiana implemented opioid prescribing emergency rules and stratify the changes in opioid prescribing by patient and provider subgroups. An interrupted time series analysis was conducted using data obtained from the Indiana PDMP. Prescription level data was merged with census data to characterize patient socioeconomic status. Analyses were stratified by patients’ gender, age, opioid dosage, and payer. The primary outcome indicator was the total morphine equivalent dose (MED) of dispensed opioids per day in the state of Indiana. Also considered were number of unique patients, unique providers, and prescriptions; MED per transaction and per day; and number of days supplied. After controlling for time trends, we found that total MED for opioids decreased after implementing the new emergency rules, differing by patient gender, age, and payer. The effect was larger for males than females and almost 10 times larger for 0–20 year olds as compared to the 60+ age range. Medicare and Medicaid patients experienced more decline in prescribing than patients with private insurance. Patients with prescriptions paid for by workers’ comp experienced the most significant decline. The emergency rules were associated with decline in both the number of prescribers and the number of day supply. Although the Indiana opioid prescribing emergency rules impacted statewide prescribing behavior across all individual patient and provider characteristics, the emergency rules’ effect was not consistent across patient characteristics. Further studies are needed to assess how individual patient characteristics influence the interpretation and application of state policies on opioid prescribing.

Objective Lung cancer is the most common cause of cancer-related death in the USA. While most patients are diagnosed following symptomatic presentation, no studies have compared symptoms and physical examination signs at or prior to diagnosis from electronic health records (EHRs) in the USA. We aimed to identify symptoms and signs in patients prior to diagnosis in EHR data. Design Case–control study. Setting Ambulatory care clinics at a large tertiary care academic health centre in the USA. Participants, outcomes We studied 698 primary lung cancer cases in adults diagnosed between 1 January 2012 and 31 December 2019, and 6841 controls matched by age, sex, smoking status and type of clinic. Coded and free-text data from the EHR were extracted from 2 years prior to diagnosis date for cases and index date for controls. Univariate and multivariable conditional logistic regression were used to identify symptoms and signs associated with lung cancer at time of diagnosis, and 1, 3, 6 and 12 months before the diagnosis/index dates. Results Eleven symptoms and signs recorded during the study period were associated with a significantly higher chance of being a lung cancer case in multivariable analyses. Of these, seven were significantly associated with lung cancer 6 months prior to diagnosis: haemoptysis (OR 3.2, 95% CI 1.9 to 5.3), cough (OR 3.1, 95% CI 2.4 to 4.0), chest crackles or wheeze (OR 3.1, 95% CI 2.3 to 4.1), bone pain (OR 2.7, 95% CI 2.1 to 3.6), back pain (OR 2.5, 95% CI 1.9 to 3.2), weight loss (OR 2.1, 95% CI 1.5 to 2.8) and fatigue (OR 1.6, 95% CI 1.3 to 2.1). Conclusions Patients diagnosed with lung cancer appear to have symptoms and signs recorded in the EHR that distinguish them from similar matched patients in ambulatory care, often 6 months or more before diagnosis. These findings suggest opportunities to improve the diagnostic process for lung cancer.

The diagnosis of lung cancer in ambulatory settings is often challenging due to non-specific clinical presentation, but there are currently no clinical quality measures (CQMs) in the United States used to identify areas for practice improvement in diagnosis. We describe the pre-diagnostic time intervals among a retrospective cohort of 711 patients identified with primary lung cancer from 2012–2019 from ambulatory care clinics in Seattle, Washington USA. Electronic health record data were extracted for two years prior to diagnosis, and Natural Language Processing (NLP) applied to identify symptoms/signs from free text clinical fields. Time points were defined for initial symptomatic presentation, chest imaging, specialist consultation, diagnostic confirmation, and treatment initiation. Median and interquartile ranges (IQR) were calculated for intervals spanning these time points. The mean age of the cohort was 67.3 years, 54.1% had Stage III or IV disease and the majority were diagnosed after clinical presentation (94.5%) rather than screening (5.5%). Median intervals from first recorded symptoms/signs to diagnosis was 570 days (IQR 273–691), from chest CT or chest X-ray imaging to diagnosis 43 days (IQR 11–240), specialist consultation to diagnosis 72 days (IQR 13–456), and from diagnosis to treatment initiation 7 days (IQR 0–36). Symptoms/signs associated with lung cancer can be identified over a year prior to diagnosis using NLP, highlighting the need for CQMs to improve timeliness of diagnosis.

Objective Lung cancer is increasingly recognised as a heterogeneous disease. Recent advances with targeted therapies for lung cancer with oncogenic mutations have greatly improved the prognosis for this subset of patients, yet little is known about their experiences. This study aimed to identify the needs and explore the healthcare experiences of these advanced patients with oncogenic mutation driven lung cancer. Design Qualitative interviews with patients with advanced or metastatic non-small cell lung cancer with oncogenic alterations in anaplastic lymphoma kinase, epidermal growth factor receptor or c-ros oncogene 1. Settings Patients were recruited from online lung cancer support groups within the USA. Interviews were conducted remotely or in person, transcribed verbatim and analysed using an iterative inductive and deductive process. Participants We included 39 patients (11 males and 28 females) with a median age of 48. Results Two primary theme categories emerged: patients' unmet needs and improving healthcare experiences. Unmet needs are related to patients’ desire to view their disease as a chronic illness, aspire to live a meaningful existence without financial devastation, desire for understanding along with emotional support and needing help with practical matters. Improving healthcare experiences involved patients’ desire to trust the expertise of clinical providers, receive reliable care and be treated holistically and as informed partners. Conclusions Patients with lung cancer with oncogenic mutations live uncharted experiences. Targeted therapy brings hope, but uncertainty is daunting. Patients grapple with the meaning and purpose of their lives while day-to-day obligations remain challenging. Healthcare teams are instrumental in their care experiences, and patients desire providers who are up-to-date on advances in the field and treat them as whole persons.