Faculty Bibliography

OBJECTIVES/OBJECTIVE:To evaluate the feasibility and efficacy of a workflow designed to increase the number of patients counseled and initiated on the HPV vaccination series among an underserved patient population presenting for abortion care. METHODS:A retrospective chart review was conducted for 6 months before implementation to determine baseline rates of counseling and vaccine uptake. A workflow was prospectively implemented for 31 weeks at a resident-run urban safety net hospital abortion clinic. Rates of HPV vaccine-eligible patients who were counseled on vaccination were recorded along with rates of those accepting the vaccine who initiated and completed the series. RESULTS:Following implementation, the rate of eligible patients receiving counseling on the HPV vaccine increased from 23.8% to 68.7%. There was a 400% relative increase in the rate of patients receiving at least 1 dose of the vaccine from 6.8% to 34%. Forty-one (41.4%) patients due for a subsequent dose received at least 1 additional dose. Fifteen (14.7%) patients who received at least 1 dose of the HPV vaccine completed the series. The most common primary language among vaccinated patients was Spanish (66.7%). A majority (81.8%) identified their race as Hispanic or Latine, followed by Black (8%), and 13 ethnic backgrounds were self-identified. CONCLUSIONS:Implementation of an HPV vaccination workflow in an abortion clinic was feasible and resulted in substantial increases in counseling and uptake of the vaccine. Abortion care represents an opportunity to address HPV vaccination gaps, particularly among medically under-resourced populations most at risk for cervical cancer disparities.

PURPOSE/OBJECTIVE:The National Academy of Science Engineering and Medicine (NASEM) developed items to collect sexual orientation and gender identity (SOGI) in healthcare settings to harmonize collection of these data and address disparities often experienced by sexual and gender minorities (SGM) (LGBTQAI+). This study tested wording of SOGI items among the SGM Community. METHODS:Individuals were recruited to participate in an interview about the NASEM SOGI items. Eligible participants identified as SGM, lived within the catchment area of an NYC academic medical center, had a history of cancer, or were caregivers of a person with cancer. Interviews were audio-recorded, transcribed, and qualitatively coded. RESULTS:Thirty-eight SGM individuals participated. The majority disliked the options for sexual orientation (SO) and gender identity (GI) but did find one they would choose. For SO, participants thought options like queer, pansexual, and asexual were missing, and for GI, participants said non-binary and transgender category (transgender man, transgender woman) were needed. Half said they had no concerns about disclosing SOGI information on medical intake forms and others reported preferring knowing why it was needed and who would have access. Several expressed worry about their safety upon disclosure of SOGI. Respondents cited being less likely to disclose SOGI if there was an offensive question on intake form (e.g., spouse instead of partner) or if there were no privacy assurances. Almost all expected reported SOGI to be reflected in their oncology healthcare. CONCLUSIONS:The NASEM questions need improvement. To improve trust and encourage disclosure, clinicians and clinics should improve the options for SOGI data collection and take steps to ensure privacy is addressed.

BACKGROUND/UNASSIGNED:Significant disparities exist in the care of patients with gynecologic malignancies. Higher incidences of gynecologic malignancies among underrepresented subpopulations (eg, racial, ethnic, and/or LGBTQAI+) and lack of representative enrollment within clinical trials have highlighted the need to improve healthcare equity. We aimed to identify barriers to equitable health care and clinical trial participation for specific diverse populations of patients with gynecologic malignancies and to identify potential solutions for overcoming these barriers. METHODS/UNASSIGNED:A series of 4 live and 3 asynchronous advisory boards facilitated by GSK was conducted between January 2023 and July 2024; live advisory boards were population specific. Gynecologic oncologists, health researchers, advanced practice providers, patients, and patient advocacy group representatives who worked with and/or were themselves members of the focus population participated. Insights were compiled and analyzed to identify barriers and potential solutions across and within populations. RESULTS/UNASSIGNED:Common barriers to equitable health care across all populations included cost, transportation, level of health literacy, and provider biases; 11 population-specific barriers were noted, with LGBTQAI+ patients described as facing the most barriers. Patient navigator involvement was identified as a feasible and highly impactful solution for breaking multiple barriers across various diverse populations. CONCLUSIONS/UNASSIGNED:Most barriers to equitable health care were population specific, affirming the need for continued consultation and discussions with members of communities and with individuals to address specific barriers and enact effective solutions. Engagement of patient navigators was identified as an important way to improve disparities within the care of gynecologic malignancies across all underrepresented patients.

BACKGROUND:Routine collection and use of sexual orientation and gender identity data can assist in understanding and addressing the health disparities that affect lesbian, gay, bisexual, transgender, queer+ (LGBTQ+), also known as sexual and gender minority, individuals and communities. This study explored the implementation of a culturally relevant sexual and gender minority/sexual orientation and gender identity training program at a National Cancer Institute (NCI)-Designated Comprehensive Cancer Center. METHODS:The training consisted of 6 in-person 15-minute modules or 3 virtual 30-minute modules that occurred during established high-reliability organization huddles attended by oncology faculty and staff. Module topics were (1) Building LGBTQ+ Knowledge & LGBTQ+ Cancer Disparities, (2) Creating an Inclusive Environment, (3) Recovering From Misgendering/Making Assumptions, (4) How to Receive & Respond to Feedback, (5) Witnessing & Responding to Discrimination, and (6) Making and Sustaining a Change. All high-reliability organization attendees were considered eligible for participation and were provided with pretraining and post-training surveys. Survey items included comfort caring for sexual and gender minority patients, practice collecting sexual orientation and gender identity data, knowledge of sexual and gender minority health, and demographics. RESULTS:A total of 344 individuals completed the presurvey and 187 completed the postsurvey. Postsurvey results demonstrated a statistically significant improvement in self-perceived knowledge about sexual and gender minority health (scale: 0-100, with 100 = highest; presurvey vs postsurvey, 69 vs 84; P < .001). Respondents also reported statistically significant improvements in confidence in engaging with sexual orientation and gender identity questions (53 vs 79, P < .001) as well as intention to collect patient sexual orientation and gender identity information (49 vs 75, P < .001). Notably, sexual orientation and gender identity data collection tracking demonstrated a 311% increase in sexual orientation and 262% in gender identity disclosure during the study period. CONCLUSION/CONCLUSIONS:Despite the availability of sexual orientation and gender identity data fields within electronic health records, sexual orientation and gender identity disclosure remains an ongoing nationwide problem. Use of culturally relevant sexual and gender minority/sexual orientation and gender identity training can help improve oncology staff and clinician sexual and gender minority knowledge and confidence when engaging patients with and subsequent documentation of sexual orientation and gender identity data, resulting in improvement of data completion.

Many studies have addressed the inequities of gender within medicine. And although more attention has been brought to this topic in the past couple of decades, studies demonstrate that there is an equity gap in the workplace, in the research sphere, and in pay compensation. Internet searches prove that leadership in academic spaces as well as private practice both remain predominantly male. As an example, the field of gynecologic oncology is a field that specifically addresses and serves the health needs of patients who identify as women. However, although the specialty should be at the forefront of the effort to address gender inequities, it still has considerable progress to make in this area. This article seeks to describe the literature regarding gender disparities in medicine, and what gender equity can look like while laying out strategies to address the inequities that persist - using gynecologic oncology as an example.

OBJECTIVE:Artificial Intelligence (AI) systems such as ChatGPT can take medical examinations and counsel patients regarding medical diagnosis. We aim to quantify the accuracy of the ChatGPT V3.4 in answering commonly asked questions pertaining to genetic testing and counseling for gynecologic cancers. METHODS:Forty questions were formulated in conjunction with gynecologic oncologists and adapted from professional society guidelines and ChatGPT version 3.5 was queried, the version that is readily available to the public. The two categories of questions were genetic counseling guidelines and questions pertaining to specific genetic disorders. The answers were scored by two attending Gynecologic Oncologists according to the following scale: 1) correct and comprehensive, 2) correct but not comprehensive, 3) some correct, some incorrect, and 4) completely incorrect. Scoring discrepancies were resolved by additional third reviewer. The proportion of responses earning each score were calculated overall and within each question category. RESULTS:ChatGPT provided correct and comprehensive answers to 33/40 (82.5%) questions, correct but not comprehensive answers to 6/40 (15%) questions, partially incorrect answers to 1/40 (2.5%) questions, and completely incorrect answers to 0/40 (0%) questions. The genetic counseling category of questions had the highest proportion of answers that were both correct and comprehensive with ChatGPT answering all 20/20 questions with 100% accuracy and were comprehensive in responses. ChatGPT performed equally in the specific genetic disorders category, with 88.2% (15/17) and 66.6% (2/3) correct and comprehensive answers to questions pertaining to hereditary breast and ovarian cancer and Lynch syndrome questions respectively. CONCLUSION/CONCLUSIONS:ChatGPT accurately answers questions about genetic syndromes, genetic testing, and counseling in majority of the studied questions. These data suggest this powerful tool can be utilized as a patient resource for genetic counseling questions, though more data input from gynecologic oncologists would be needed to educate patients on genetic syndromes.

OBJECTIVE:To quantify the accuracy of ChatGPT in answering commonly asked questions pertaining to cervical cancer prevention, diagnosis, treatment, and survivorship/quality-of-life (QOL). METHODS:ChatGPT was queried with 64 questions adapted from professional society websites and the authors' clinical experiences. The answers were scored by two attending Gynecologic Oncologists according to the following scale: 1) correct and comprehensive, 2) correct but not comprehensive, 3) some correct, some incorrect, and 4) completely incorrect. Scoring discrepancies were resolved by additional reviewers as needed. The proportion of responses earning each score were calculated overall and within each question category. RESULTS:ChatGPT provided correct and comprehensive answers to 34 (53.1%) questions, correct but not comprehensive answers to 19 (29.7%) questions, partially incorrect answers to 10 (15.6%) questions, and completely incorrect answers to 1 (1.6%) question. Prevention and survivorship/QOL had the highest proportion of "correct" scores (scores of 1 or 2) at 22/24 (91.7%) and 15/16 (93.8%), respectively. ChatGPT performed less well in the treatment category, with 15/21 (71.4%) correct scores. It performed the worst in the diagnosis category with only 1/3 (33.3%) correct scores. CONCLUSION/CONCLUSIONS:ChatGPT accurately answers questions about cervical cancer prevention, survivorship, and QOL. It performs less accurately for cervical cancer diagnosis and treatment. Further development of this immensely popular large language model should include physician input before it can be utilized as a tool for Gynecologists or recommended as a patient resource for information on cervical cancer diagnosis and treatment.

BACKGROUND:Sexual orientation and gender identity (SOGI) data collection in community oncology practices is critical to identify and address cancer inequities, but less than 20% of NCI Community Oncology Research Program (NCORP)-affiliated practices regularly collect SOGI data despite widespread recommendations. We evaluated multilevel barriers and facilitators for SOGI data collection at NCORP practices. METHODS:We conducted 14 semi-structured interviews at seven purposefully sampled NCORP oncology practices. We interviewed one clinician (oncologist, advanced practice provider) and one clinic staff member per practice. Thematic analysis informed by the Consolidated Framework for Implementation Research (CFIR) was conducted to identify barriers and facilitators. RESULTS:Thematic saturation occurred after interviews at six practices and was confirmed with interviews at an additional practice. Participants highlighted multilevel barriers including low levels of understanding, information technology infrastructure, and perceived low relative priority. Not understanding the role of SOGI data in oncology care contributed to cis-heteronormative culture. At the clinic level, this culture coincided with a lack of processes and policies for collecting SOGI from all patients. At the care team level, perceived irrelevance to oncology care was related to discomfort asking SOGI, fear of patient discomfort, and limited awareness of SOGI in electronic health records. Suggested solutions included: normalizing asking SOGI questions, giving patients privacy to complete SOGI, and clarifying clinical relevance. CONCLUSIONS:SOGI data collection barriers stemmed from perceptions that SOGI disclosure does not influence care quality. Oncology teams may benefit from training on culturally sensitive SOGI collection, education on SOGI data relevance to oncology practices, and support for implementing SOGI data collection policies.