Assessing the Seasonality of Lab Tests Among Patients with Alzheimer's Disease and Related Dementias in OneFlorida Data Trust.

About 1 in 9 older adults over 65 has Alzheimer's disease (AD), many of whom also have multiple other chronic conditions such as hypertension and diabetes, necessitating careful monitoring through laboratory tests. Understanding the patterns of laboratory tests in this population aids our understanding and management of these chronic conditions along with AD. In this study, we used an unimodal cosinor model to assess the seasonality of lab tests using electronic health record (EHR) data from 34,303 AD patients from the OneFlorida+ Clinical Research Consortium. We observed significant seasonal fluctuations-higher in winter in lab tests such as glucose, neutrophils per 100 white blood cells (WBC), and WBC. Notably, certain leukocyte types like eosinophils, lymphocytes, and monocytes are elevated during summer, likely reflecting seasonal respiratory diseases and allergens. Seasonality is more pronounced in older patients and varies by gender. Our findings suggest that recognizing these patterns and adjusting reference intervals for seasonality would allow healthcare providers to enhance diagnostic precision, tailor care, and potentially improve patient outcomes.

Quality of Answers of Generative Large Language Models Versus Peer Users for Interpreting Laboratory Test Results for Lay Patients: Evaluation Study.

BACKGROUND: Although patients have easy access to their electronic health records and laboratory test result data through patient portals, laboratory test results are often confusing and hard to understand. Many patients turn to web-based forums or question-and-answer (Q&A) sites to seek advice from their peers. The quality of answers from social Q&A sites on health-related questions varies significantly, and not all responses are accurate or reliable. Large language models (LLMs) such as ChatGPT have opened a promising avenue for patients to have their questions answered. OBJECTIVE: We aimed to assess the feasibility of using LLMs to generate relevant, accurate, helpful, and unharmful responses to laboratory test-related questions asked by patients and identify potential issues that can be mitigated using augmentation approaches. METHODS: We collected laboratory test result-related Q&A data from Yahoo! Answers and selected 53 Q&A pairs for this study. Using the LangChain framework and ChatGPT web portal, we generated responses to the 53 questions from 5 LLMs: GPT-4, GPT-3.5, LLaMA 2, MedAlpaca, and ORCA_mini. We assessed the similarity of their answers using standard Q&A similarity-based evaluation metrics, including Recall-Oriented Understudy for Gisting Evaluation, Bilingual Evaluation Understudy, Metric for Evaluation of Translation With Explicit Ordering, and Bidirectional Encoder Representations from Transformers Score. We used an LLM-based evaluator to judge whether a target model had higher quality in terms of relevance, correctness, helpfulness, and safety than the baseline model. We performed a manual evaluation with medical experts for all the responses to 7 selected questions on the same 4 aspects. RESULTS: Regarding the similarity of the responses from 4 LLMs; the GPT-4 output was used as the reference answer, the responses from GPT-3.5 were the most similar, followed by those from LLaMA 2, ORCA_mini, and MedAlpaca. Human answers from Yahoo data were scored the lowest and, thus, as the least similar to GPT-4-generated answers. The results of the win rate and medical expert evaluation both showed that GPT-4's responses achieved better scores than all the other LLM responses and human responses on all 4 aspects (relevance, correctness, helpfulness, and safety). LLM responses occasionally also suffered from lack of interpretation in one's medical context, incorrect statements, and lack of references. CONCLUSIONS: By evaluating LLMs in generating responses to patients' laboratory test result-related questions, we found that, compared to other 4 LLMs and human answers from a Q&A website, GPT-4's responses were more accurate, helpful, relevant, and safer. There were cases in which GPT-4 responses were inaccurate and not individualized. We identified a number of ways to improve the quality of LLM responses, including prompt engineering, prompt augmentation, retrieval-augmented generation, and response evaluation.

Quality of Answers of Generative Large Language Models vs Peer Patients for Interpreting Lab Test Results for Lay Patients: Evaluation Study.

Background: Even though patients have easy access to their electronic health records and lab test results data through patient portals, lab results are often confusing and hard to understand. Many patients turn to online forums or question and answering (Q&A) sites to seek advice from their peers. However, the quality of answers from social Q&A on health-related questions varies significantly, and not all the responses are accurate or reliable. Large language models (LLMs) such as ChatGPT have opened a promising avenue for patients to get their questions answered. Objective: We aim to assess the feasibility of using LLMs to generate relevant, accurate, helpful, and unharmful responses to lab test-related questions asked by patients and to identify potential issues that can be mitigated with augmentation approaches. Methods: We first collected lab test results related question and answer data from Yahoo! Answers and selected 53 Q&A pairs for this study. Using the LangChain framework and ChatGPT web portal, we generated responses to the 53 questions from four LLMs including GPT-4, Meta LLaMA 2, MedAlpaca, and ORCA_mini. We first assessed the similarity of their answers using standard QA similarity-based evaluation metrics including ROUGE, BLEU, METEOR, BERTScore. We also utilized an LLM-based evaluator to judge whether a target model has higher quality in terms of relevance, correctness, helpfulness, and safety than the baseline model. Finally, we performed a manual evaluation with medical experts for all the responses of seven selected questions on the same four aspects. Results: Regarding the similarity of the responses from 4 LLMs, where GPT-4 output was used as the reference answer, the responses from LLaMa 2 are the most similar ones, followed by LLaMa 2, ORCA_mini, and MedAlpaca. Human answers from Yahoo data were scored lowest and thus least similar to GPT-4-generated answers. The results of Win Rate and medical expert evaluation both showed that GPT-4's responses achieved better scores than all the other LLM responses and human responses on all the four aspects (relevance, correctness, helpfulness, and safety). However, LLM responses occasionally also suffer from lack of interpretation in one's medical context, incorrect statements, and lack of references. Conclusions: By evaluating LLMs in generating responses to patients' lab test results related questions, we find that compared to other three LLMs and human answer from the Q&A website, GPT-4's responses are more accurate, helpful, relevant, and safer. However, there are cases that GPT-4 responses are inaccurate and not individualized. We identified a number of ways to improve the quality of LLM responses including prompt engineering, prompt augmentation, retrieval augmented generation, and response evaluation.

Towards Interpretable Multimodal Predictive Models for Early Mortality Prediction of Hemorrhagic Stroke Patients.

The increasing death rate over the past eight years due to stroke has prompted clinicians to look for data-driven decision aids. Recently, deep-learning-based prediction models trained with fine-grained electronic health record (EHR) data have shown superior promise for health outcome prediction. However, the use of EHR-based deep learning models for hemorrhagic stroke outcome prediction has not been extensively explored. This paper proposes an ensemble deep learning framework to predict early mortality among ICU patients with hemorrhagic stroke. The proposed ensemble model achieved an accuracy of 83%, which was higher than the fusion model and other baseline models (logistic regression, decision tree, random forest, and XGBoost). Moreover, we used SHAP values for interpretation of the ensemble model to identify important features for the prediction. In addition, this paper follows the MINIMAR (MINimum Information for Medical AI Reporting) standard, presenting an important step towards building trust among the AI system and clinicians.

Specialty-Specific Entrustable Professional Activities: A Bridge to Internship.

Background Undergraduate medical education aims to prepare learners to become capable residents. New interns are expected to perform clinical tasks with distant supervision reliant on having acquired a medical degree. However, there is limited data to discuss what entrustment residency programs grant versus what the medical schools believe they have trained their graduates to perform. At our institution, we sought to foster an alliance between undergraduate medical education (UME) and graduate medical education (GME) toward specialty-specific entrustable professional activities (SSEPAs). These SSEPAs create a bridge to residency and help students structure the final year of medical school while striving for entrustability for day one of residency. This paper describes the SSEPA curriculum development process and student self-assessment of competence. Methodology We piloted an SSEPA program with the departments of Family Medicine, Internal Medicine, Neurology, and Obstetrics & Gynecology. Utilizing Kern's curriculum development framework, each specialty designed a longitudinal curriculum with a post-match capstone course. Students participated in pre-course and post-course self-assessments utilizing the Chen scale for each entrustable professional activity (EPA). Results A total of 42 students successfully completed the SSEPA curriculum in these four specialties. Students' self-assessed competence levels rose from 2.61 to 3.65 in Internal Medicine; 3.23 to 4.12 in Obstetrics and Gynecology; 3.62 to 4.13 in Neurology; and 3.65 to 3.79 in Family Medicine. Students across all specialties noted an increase in confidence from 3.45 to 4.38 in Internal Medicine; 3.3 to 4.6 in Obstetrics and Gynecology; 3.25 to 4.25 in Neurology; and 4.33 to 4.67 in Family Medicine. Conclusions A specialty-specific curriculum utilizing a competency-based framework for learners traversing the UME to GME journey in the final year of medical school improves learner confidence in their clinical abilities and may lead to an improved educational handoff between UME and GME.

Early Performance of the Patients Over Paperwork Initiative among Family Medicine Physicians.

OBJECTIVES: In 2019, the Centers for Medicare & Medicaid Services began implementing the Patients Over Paperwork (POP) initiative in response to clinicians reporting burdensome documentation regulations. To date, no study has evaluated how these policy changes have influenced documentation burden. METHODS: Our data came from the electronic health records of an academic health system. Using quantile regression models, we assessed the association between the implementation of POP and clinical documentation word count using data from family medicine physicians in an academic health system from January 2017 to May 2021 inclusive. Studied quantiles included the 10th, 25th, 50th, 75th, and 90th quantiles. We controlled for patient-level (race/ethnicity, primary language, age, comorbidity burden), visit-level (primary payer, level of clinical decision making involved, whether a visit was done through telemedicine, whether a visit was for a new patient), and physician-level (sex) characteristics. RESULTS: We found that the POP initiative was associated with lower word counts across all of the quantiles. In addition, we found lower word counts among notes for private payers and telemedicine visits. Conversely, higher word counts were observed in notes that were written by female physicians, notes for new patient visits, and notes involving patients with greater comorbidity burden. CONCLUSIONS: Our initial evaluation suggests that documentation burden, as measured by word count, has declined over time, particularly following implementation of the POP in 2019. Additional research is needed to see whether the same occurs when examining other medical specialties, clinician types, and longer evaluation periods.

Merit-based incentive payment system participation and after-hours documentation among US office-based physicians: Findings from the 2021 National Electronic Health Records Survey.

BACKGROUND: After-hours documentation burden among US clinicians is often uncompensated work and has been associated with burnout, leading health systems to identify root causes and seek interventions to reduce this. A few studies have suggested quality programme participation (e.g., Merit-Based Incentive Payment System [MIPS]) was associated with a higher administrative burden. However, the association between MIPS participation and after-hours documentation has not been fully explored. Thus, this study aims to assess whether participation in the MIPS programme was independently associated with after-hours documentation burden. METHODS: We used 2021 data from the National Electronic Health Records Survey. We used a multivariable ordinal logistic regression model to assess whether MIPS participation was associated with the amount of after-hours documentation burden when controlling for other factors. We controlled for physician age, specialty, sex, number of practice locations, number of physicians, practice ownership, whether team support (e.g., scribes) is used for documentation tasks, and whether the practice accepts Medicaid patients. RESULTS: We included 1801 office-based US physician respondents with complete data for variables of interest. After controlling for other factors, MIPS participation was associated with greater odds of spending a greater number of hours on after-hours documentation (odds ratio = 1.44, 95% confidence interval 1.06-1.95). CONCLUSIONS: MIPS participation may increase after-hours documentation burden among US office-based physicians, suggesting that physicians may require additional resources to more efficiently report data.

Trauma-informed patient and public-engaged research: Development and evaluation of an online training programme.

INTRODUCTION: As patients, members of the public, and professional stakeholders engage in co-producing health-related research, an important issue to consider is trauma. Trauma is very common and associated with a wide range of physical and behavioural health conditions. Thus, it may benefit research partnerships to consider its impact on their stakeholders as well as its relevance to the health condition under study. The aims of this article are to describe the development and evaluation of a training programme that applied principles of trauma-informed care (TIC) to patient- and public-engaged research. METHODS: A research partnership focused on addressing trauma in primary care patients ('myPATH') explicitly incorporated TIC into its formation, governance document and collaborative processes, and developed and evaluated a free 3-credit continuing education online training. The training was presented by 11 partners (5 professionals, 6 patients) and included academic content and lived experiences. RESULTS: Training participants (N = 46) positively rated achievement of learning objectives and speakers' performance (ranging from 4.39 to 4.74 on a 5-point scale). The most salient themes from open-ended comments were that training was informative (n = 12) and that lived experiences shared by patient partners were impactful (n = 10). Suggestions were primarily technical or logistical. CONCLUSION: This preliminary evaluation indicates that it is possible to incorporate TIC principles into a research partnership's collaborative processes and training about these topics is well-received. Learning about trauma and TIC may benefit research partnerships that involve patients and public stakeholders studying a wide range of health conditions, potentially improving how stakeholders engage in co-producing research as well as producing research that addresses how trauma relates to their health condition under study. PATIENT OR PUBLIC CONTRIBUTION: The myPATH Partnership includes 22 individuals with professional and lived experiences related to trauma (https://www.usf.edu/cbcs/mhlp/centers/mypath/); nine partners were engaged due to personal experiences with trauma; other partners are community-based providers and researchers. All partners contributed ideas that led to trauma-informed research strategies and training. Eleven partners (5 professionals, 6 patients) presented the training, and 12 partners (8 professionals, 4 patients) contributed to this article and chose to be named as authors.

Annotation and Information Extraction of Consumer-Friendly Health Articles for Enhancing Laboratory Test Reporting.

Viewing laboratory test results is patients' most frequent activity when accessing patient portals, but lab results can be very confusing for patients. Previous research has explored various ways to present lab results, but few have attempted to provide tailored information support based on individual patient's medical context. In this study, we collected and annotated interpretations of textual lab result in 251 health articles about laboratory tests from AHealthyMe.com. Then we evaluated transformer-based language models including BioBERT, ClinicalBERT, RoBERTa, and PubMedBERT for recognizing key terms and their types. Using BioPortal's term search API, we mapped the annotated terms to concepts in major controlled terminologies. Results showed that PubMedBERT achieved the best F1 on both strict and lenient matching criteria. SNOMED CT had the best coverage of the terms, followed by LOINC and ICD-10-CM. This work lays the foundation for enhancing the presentation of lab results in patient portals by providing patients with contextualized interpretations of their lab results and individualized question prompts that they can, in turn, refer to during physician consults.

Patients' use of smartphone apps for health record access in 2019: A cross-sectional study.

INTRODUCTION: The 21st Century Cures Act has expanded patients' access to portals through smartphone applications (apps). To date, the prevalence of patient portal smartphone apps use is unclear, especially on a national scale. METHODS: Using the 2019 Health Information National Trends Survey, we assessed factors associated with patient portal adopters accessing their records through a smartphone app. Multivariable logistic regression models were conducted and we reported results using predicted probability. RESULTS: Across a weighted sample of 75,324,288 respondents, 39 % reported using a smartphone app to access their health records. Adults with smartphone-only internet (40.0 %; 95 % CI: 35.4-33.3) were more likely to use a smartphone app compared to adults with home internet access (30.6 %; 95 % CI: 27.9-44.7). CONCLUSIONS: Optimizing the implementation and delivery of patient portal content via smartphone apps may improve their reach to patients.

Cancer Screening Among Rural and Urban Clinics During COVID-19: A Multistate Qualitative Study.

PURPOSE: The effects of COVID-19 have been understudied in rural areas. This study sought to (1) identify cancer screening barriers and facilitators during the pandemic in rural and urban primary care practices, (2) describe implementation strategies to support cancer screening, and (3) provide recommendations. METHODS: A qualitative study was conducted (N = 42) with primary care staff across 20 sites. Individual interviews were conducted through videoconference from August 2020 to April 2021 and recorded, transcribed, and analyzed using deductive and inductive coding (hybrid approach) in NVivo 12 Plus. Practices included federally qualified health centers, tribal health centers, rural health clinics, hospital/health system-owned clinics, and academic medical centers across 10 states including urban (55%) and rural (45%) sites. Staff included individuals serving in the dual role of health care provider and administrator (21.4%), health care administrator (23.8%), physician (19.0%), advanced practice provider (11.9%), or resident (23.8%). The interviews assessed perceptions about cancer screening barriers and facilitators, implementation strategies, and future recommendations. RESULTS: Participants reported multilevel barriers to cancer screening including policy-level (eg, elective procedure delays), organizational (eg, backlogs), and individual (eg, patient cancellation). Several facilitators to screening were noted, such as home-based testing, using telehealth, and strong partnerships with referral sites. Practices used strategies to encourage screening, such as incentivizing patients and providers and expanding outreach. Rural clinics reported challenges with backlogs, staffing, telehealth implementation, and patient outreach. CONCLUSION: Primary care staff used innovative strategies during the pandemic to promote cancer screening. Unresolved challenges (eg, backlogs and inability to implement telehealth) disproportionately affected rural clinics.

Prevalence and Factors Associated with Patient-Requested Corrections to the Medical Record through Use of a Patient Portal: Findings from a National Survey.

BACKGROUND: Providing patients with medical records access is one strategy that health systems can utilize to reduce medical errors. However, how often patients request corrections to their records on a national scale is unknown. OBJECTIVES: We aimed to develop population-level estimates of patients who request corrections to their medical records using national-level data. We also identified patient-level correlates of requesting corrections. METHODS: We used the 2017 and 2019 Health Information National Trends Survey and examined all patient portal adopters. We applied jackknife replicate weights to develop population-representative estimates of the prevalence of requesting medical record corrections. We conducted a multivariable logistic regression analysis to identify correlates of requesting corrections while controlling for demographic factors, health care utilization patterns, health status, technology/internet use patterns, and year. RESULTS: Across 1,657 respondents, 125 (weighted estimate: 6.5%) reported requesting corrections to their medical records. In unadjusted models, greater odds of requesting corrections were observed among patients who reported their race/ethnicity as non-Hispanic black (odds ratio [OR]: 2.20, 95% confidence interval [CI]: 1.10-4.43), had frequent portal visits (OR: 3.92, 95% CI: 1.51-10.23), and had entered data into the portal (OR: 7.51, 95% CI: 4.08-13.81). In adjusted models, we found greater odds of requesting corrections among those who reported frequent portal visits (OR: 3.39, 95% CI: 1.24-9.33) and those who reported entering data into the portal (OR: 6.43, 95% CI: 3.20-12.94). No other significant differences were observed. CONCLUSION: Prior to the Information Blocking Final Rule in April 2021, approximately 6.5% of patients requested corrections of errors in their medical records at the national level. Those who reported higher engagement with their health, as proxied by portal visit frequency and entering data into the portal, were more likely to request corrections.

Mammogram Order Completion Rates Among Women with Diabetes.

INTRODUCTION: Breast cancer is one of the leading causes of death among women residing in the United States. Early detection through mammogram screening can decrease the morbidity and mortality associated with the disease. For women with diabetes, however, incidence and mortality rates of breast cancer are increased. METHODS: This was a retrospective examination, identifying orders and completion of mammogram among patients with and without diabetes, 2015 to 2019, through the electronic health record. Diabetes and other factors were identified as possible predictors of completion. RESULTS: Of the 16,688 patients who were included in this study, only 54.5% successfully completed mammography orders prescribed by their primary care physician. The 40 to 49 age group had the highest order completion rate at 57.6%. The prevalence of diabetes in this sample was 21.3%. Overall, 51.6% of patients with diabetes completed mammogram orders compared with 55.3% of patients without diabetes. DISCUSSION: Patients with diabetes were significantly less likely to complete mammogram screenings (51.6%) compared with patients without diabetes (55.3%), despite there being an increased incidence of breast cancer among patients with diabetes. Factors such as the lack of access to treatment centers, affordability, patient education, among others may have contributed to low completion rates.

Erectile dysfunction and prostate diseases are the predominant Google search terms amongst men's health topics.

Patients are becoming increasingly active consumers of health information on the internet with urologic concerns being no exception. Our objective was to explore online search trends for topics related to men's health and identify information-seeking patterns related to news and media coverage of these topics. We used Google Trends ( http://google.com/trends ) to explore search trends for various search terms related to men's health in the United States over a 5-year period. Search queries provided graphs depicting search volume as a function of time, geographical data, and related topics and queries. Isolated spikes in search volume were further explored to identify a related event. Erectile dysfunction was the most-searched topic over the last 5 years in the United States. Prostate cancer and benign prostatic hyperplasia were the second and third most-searched topics, respectively. Other popular topics involved symptoms or pathologies of the testicles and penis. Most topics had relatively stable search volumes, with the exceptions of premature ejaculation and Peyronie's disease. Several observed spikes in search volume were attributable to singular events, mostly in the form of online article publications or social media posts. We believe it may be helpful for providers to stay informed of cultural events relating to medical conditions to anticipate patient concerns.

Rapid adaptation of cancer screening practices during COVID-19: A multi-state qualitative study.

Context: The COVID-19 pandemic required primary care practices to rapidly adapt cancer screening procedures to comply with changing guidelines and policies. Objective: This study sought to: 1) identify cancer screening barriers and facilitators during the COVID-19 pandemic; 2) describe cancer screening adaptations; and 3) provide recommendations. Study design: A qualitative study was conducted (n= 42) with primary care staff. Individual interviews were conducted through videoconference from August 2020 - April 2021 and recorded, transcribed, and analyzed for themes using NVivo 12 Plus. Setting: Primary care practices included federally qualified health centers, tribal health centers, rural health clinics, hospital/health system-owned, and academic medical centers located across ten states including urban (55%) and rural (45%) sites. Population studied: Primary care staff included physicians (n=13), residents (n=10), advanced practice providers (n=9), and administrators (n=10). Outcome measures: The interviews assessed perceptions about cancer screening barriers and facilitators, necessary adaptations, and future recommendations. Results: Barriers to cancer screening included delays in primary and specialty care, staff shortages, lack of personal protective equipment, patient hesitancy to receive in-person care, postal service delays for mail-home testing, COVID-19 travel restrictions (for Mexico-US border-crossing patients) and organizational policies (e.g., required COVID-19 testing prior to screening). Facilitators included better care coordination and collaboration due to the pandemic and more time during telehealth visits to discuss cancer screening compared to in-person visits. Adaptations included delayed screening, patient triage (e.g., prioritizing patients overdue for screening), telehealth visits to discuss cancer screening, mail-home testing, coordinating cancer screenings (e.g., providing fecal immunochemical test materials during cervical cancer screening) and same-day cancer screening. Recommendations included more public health education about the importance of cancer screening during COVID-19, more mail-home testing, and expanded healthcare access (e.g., weekend clinic) to address patient backlogs for cancer screening. Conclusions: Primary care staff developed innovative strategies to adapt cancer screening during the COVID-19 pandemic. Unresolved challenges (e.g., patient backlogs) will require additional implementation stra.

Primary care physicians' electronic health record proficiency and efficiency behaviors and time interacting with electronic health records: a quantile regression analysis.

OBJECTIVE: This study aimed to understand the association between primary care physician (PCP) proficiency with the electronic health record (EHR) system and time spent interacting with the EHR. MATERIALS AND METHODS: We examined the use of EHR proficiency tools among PCPs at one large academic health system using EHR-derived measures of clinician EHR proficiency and efficiency. Our main predictors were the use of EHR proficiency tools and our outcomes focused on 4 measures assessing time spent in the EHR: (1) total time spent interacting with the EHR, (2) time spent outside scheduled clinical hours, (3) time spent documenting, and (4) time spent on inbox management. We conducted multivariable quantile regression models with fixed effects for physician-level factors and time in order to identify factors that were independently associated with time spent in the EHR. RESULTS: Across 441 primary care physicians, we found mixed associations between certain EHR proficiency behaviors and time spent in the EHR. Across EHR activities studied, QuickActions, SmartPhrases, and documentation length were positively associated with increased time spent in the EHR. Models also showed a greater amount of help from team members in note writing was associated with less time spent in the EHR and documenting. DISCUSSION: Examining the prevalence of EHR proficiency behaviors may suggest targeted areas for initial and ongoing EHR training. Although documentation behaviors are key areas for training, team-based models for documentation and inbox management require further study. CONCLUSIONS: A nuanced association exists between physician EHR proficiency and time spent in the EHR.

Prevalence of, Qualities, and Barriers Associated with Mentoring Relationships from Medical Students' Perspective: A Multi-Institutional Cross-Sectional Study.

OBJECTIVES: Reports of medical student mentorship prevalence range between 26% and 77%. This broad range likely reflects the tendencies of studies to focus on specific populations of medical students. There is little consensus about the characteristics of mentoring relationships among medical students. The primary goal of this study was to determine the reported prevalence of mentorship among medical students in the United States. The secondary goals were to assess the desired qualities of and barriers to successful mentoring from a medical student perspective. METHODS: A cross-sectional online survey was administered via Qualtrics to all medical students at participating accredited medical schools from July 2018 to March 2019. The questionnaire contained a subsection of questions that assessed the existence of mentoring, facilitators, and barriers in finding a mentor, and the desired qualities of a successful mentor. RESULTS: With a 94% completion rate, 369 (69%) of 532 medical students reported having a mentor. Adjusted analysis showed that fourth-year medical students were significantly more likely to have a mentor compared with first-year (odds ratio [OR] 2.65, 95% confidence interval [CI] 1.49-4.73, P = 0.001), second-year (OR 2.07, 95% CI 1.14-3.76, P = 0.016), and third-year medical students (OR 2.16, 95% CI 1.2-3.90, P = 0.011). Compassion (64%) was the most commonly reported quality in a successful mentoring relationship. Lack of time from mentor (75%) was the most commonly reported barrier. CONCLUSIONS: This study may serve as a guide to fostering more supportive mentoring relationships. Each mentoring relationship should be tailored to the needs of the mentee, however.

27-year-old woman • postpartum seizures • PTSD • history of depression • Dx?

► Seizures with postpartum onset ► Posttraumatic stress disorder ► History of depression.