Investigator

Vanessa Lozano

Texas Christian University

VLVanessa Lozano
Papers(2)
Structure, utilizatio…Leveraging an Informa…
Collaborators(7)
Alicia M. FaszholzErnesto SosaJenny ShenJoyce C. NilandJulie HomStacy W. GraySusan Shehayeb
Institutions(4)
Texas Christian Unive…Reliant Medical GroupStony Brook UniversityCity Of Hope

Papers

Structure, utilization, and screening adherence of a student-run women’s health clinic for uninsured Spanish-speaking women: A descriptive analysis

Background: Uninsured, low-income Spanish-speaking women face systemic barriers to accessing gynecologic care, especially within Fort Worth, Texas. Because of this health disparity, we elected to evaluate screening outcomes of patients receiving care at La Clínica de las Mujeres (LCDM), a student-run clinic (SRC) providing free, culturally competent care to this population in Fort Worth, Texas. Objectives: To assess the structure and utilization of an SRC on cancer screening adherence among uninsured, Spanish-speaking women in Fort Worth, Texas. Design: Retrospective descriptive pre-post study. Methods: Chart review of patients seen at LCDM from August 2022 to September 2024 was conducted. Data included 147 clinical encounters with 114 individual patients, assessing demographics, screening history, services, and referrals. McNemar’s test assessed changes in screening adherence. Results: Patients (mean age: 47.5 years; 95.6% Hispanic) primarily resided in underserved zip codes (77.2% in 76110). Pre-intervention, 46% adhered to Pap smear guidelines and 64% to mammography guidelines. Post-intervention adherence approaches complete compliance among those with available post-intervention data (Pap χ²[1] = 66.0, p  < 0.0001; Mammogram χ²[1] = 27.0, p  < 0.0001). Services included pelvic ultrasounds ( n  = 20), specialist referrals ( n  = 11), and contraceptive access ( n  = 12). Conclusions: LCDM was associated with significant improvements in gynecologic preventive care adherence for uninsured Spanish-speaking populations in Fort Worth, Texas. Student-run models may help address critical gaps in accessibility to women’s health services and mitigate systemic barriers to care for underserved populations.

Leveraging an Informatics Approach to Identify an Unmet Clinical Need for BRCA1/2 Testing Among Patients With Ovarian Cancer

PURPOSE Although BRCA1/ 2 testing in ovarian cancer improves outcomes, it is vastly underutilized. Scalable approaches are urgently needed to improve genomically guided care. METHODS We developed a Natural Language Processing (NLP) pipeline to extract electronic medical record information to identify recipients of BRCA testing. We applied the NLP pipeline to assess testing status in 308 patients with ovarian cancer receiving care at a National Cancer Institute Comprehensive Cancer Center (main campus [MC] and five affiliated clinical network sites [CNS]) from 2017 to 2019. We compared characteristics between (1) patients who had/had not received testing and (2) testing utilization by site. RESULTS We found high uptake of BRCA testing (approximately 78%) from 2017 to 2019 with no significant differences between the MC and CNS. We observed an increase in testing over time (67%-85%), higher uptake of testing among younger patients (mean age tested = 61 years v untested = 65 years, P = .01), and higher testing among Hispanic (84%) compared with White, Non-Hispanic (78%), and Asian (75%) patients ( P = .006). Documentation of referral for an internal genetics consultation for BRCA pathogenic variant carriers was higher at the MC compared with the CNS (94% v 31%). CONCLUSION We were able to successfully use a novel NLP pipeline to assess use of BRCA testing among patients with ovarian cancer. Despite relatively high levels of BRCA testing at our institution, 22% of patients had no documentation of genetic testing and documentation of referral to genetics among BRCA carriers in the CNS was low. Given success of the NLP pipeline, such an informatics-based approach holds promise as a scalable solution to identify gaps in genetic testing to ensure optimal treatment interventions in a timely manner.

2Papers
7Collaborators