Women's Health Equity
Studying disparities in recognition, diagnosis, treatment, research representation, and health outcomes across women's whole-body health.
Research
Studying how health data can reveal what women's healthcare has missed
My developing research interests examine how clinical and biomedical data may help investigate disparities in women's health, improve clinical understanding, and support more precise and equitable care.
I'm particularly interested in longitudinal health data, clinical phenotyping, diagnostic disparities, precision medicine, and the representation of underserved and underrepresented women in healthcare data and research.
Women's Health EquityLongitudinal Health DataClinical PhenotypingDiagnostic DisparitiesBiomedical InformaticsPrecision Medicine
The Problem Space
Some disparities may be visible in the data long before they are recognized in care.
Women can move through healthcare systems for years before receiving an accurate diagnosis, appropriate treatment, or a complete explanation for their symptoms. For underserved and underrepresented women, these experiences may also intersect with racial disparities, fragmented care, research gaps, and insufficient representation in the evidence used to understand disease.
This raises questions I want to learn how to investigate. What patterns accumulate across a patient's history before a diagnosis is made? Which symptoms, encounters, laboratory findings, diagnoses, referrals, and treatment decisions might become meaningful when examined longitudinally instead of one visit at a time? Are important patterns being documented but not connected?
My research interests begin with the possibility that information distributed across years of care may contain patterns worth studying.
Research Interests
Questions I want to learn how to answer
My interests connect women's health equity with the information, methods, and technologies used to understand health and disease. Together, these areas are shaping the questions I hope to investigate through continued study and future research.
Longitudinal Health Data
Exploring how information gathered across years of care may reveal patterns, changes, and missed opportunities that are difficult to see in isolated encounters.
Clinical Phenotyping
Learning how clinical information can be organized into meaningful representations of symptoms, conditions, disease patterns, and patient trajectories.
Clinical & Biomedical Informatics
Examining how health information, biomedical knowledge, computational methods, and technology can support research and better-informed care.
Precision Medicine
Exploring how clinical, biological, environmental, and other health information may contribute to more individualized approaches to prevention, diagnosis, and treatment.
Equitable Clinical Intelligence
Questioning how decision support, algorithms, and artificial intelligence can be developed and evaluated without reproducing disparities already present in healthcare and its data.
An Evolving Research Question
How can clinical and biomedical informatics use longitudinal phenotyping to help shorten diagnostic delay in women's health?
This question represents an emerging area of interest rather than a completed research study. I'm using it to guide what I learn about research methods, statistics, clinical data, phenotyping, health disparities, and biomedical informatics.
Why this question?
Diagnostic delay can emerge across more than a single clinical encounter. Symptoms, laboratory results, diagnoses, referrals, medications, treatments, and patterns of care may accumulate across years of a patient's record.
I want to understand whether informatics methods can help researchers study those longitudinal patterns, how the patterns should be interpreted responsibly, and whether that work could contribute to earlier and more equitable recognition of disease in women.
This direction is educational and exploratory. It does not present clinical findings, diagnostic guidance, or medical advice.
Developing Foundations
Preparing to investigate the question responsibly
I'm building the healthcare, research, analytical, and informatics foundations needed to approach this direction with appropriate care and methodological discipline.
Research Literacy
Evaluating evidence carefully
Developing skills in research design, scientific literature evaluation, evidence synthesis, source quality, transparent limitations, and distinguishing findings from interpretation.
Quantitative Methods
Learning how patterns are tested
Building foundations in statistics, data analysis, measurement, analytical reasoning, and the responsible interpretation of quantitative health information.
Health Information
Understanding the record in context
Studying health information management, documentation, data quality, healthcare workflows, and the organizational conditions that shape how information is created and used.
Technical Systems
Building on an established foundation
Applying prior experience with software engineering, databases, structured data, APIs, accessibility, testing, documentation, and systems thinking to developing informatics questions.
Current Research & Learning Activity
Where the learning is happening now
My current work brings together formal education, independent inquiry, public documentation, and planned applied projects as I prepare for future research.
Formal Study
Undergraduate healthcare and data education
Pursuing a BS in Health Services Management at UMGC alongside certificates in Health Information Management & Data Analytics and Data Analytics.
Independent Inquiry
Building research literacy
Reading across women's health equity, diagnostic disparities, longitudinal health information, clinical phenotyping, biomedical informatics, and precision medicine while learning how to evaluate evidence and document limitations.
Public Learning Archive
The Informatics Diary
Documenting what I am studying, questioning, researching, and building while clearly distinguishing established evidence, interpretation, and developing knowledge.
Applied Learning
Planned educational projects
Developing project concepts that use synthetic or appropriately sourced public data to explore health-record quality, longitudinal information, care gaps, and women's health equity.
Future Inquiry
Questions that may grow from this direction
As my education and methods develop, I expect the central question to become narrower, more testable, and better grounded in specific clinical contexts and available evidence.
What patterns tend to appear before delayed recognition or diagnosis?
Exploring whether symptoms, test results, referrals, treatments, and repeated encounters form meaningful longitudinal patterns before a condition is recognized.
What information is documented, missing, fragmented, or difficult to connect?
Considering how documentation practices, data quality, system boundaries, and gaps in follow-up may affect what can be understood from a patient's history.
Whose experiences are represented in the evidence?
Examining how research participation, dataset composition, measurement choices, and clinical assumptions may affect racially underserved and underrepresented women.
How can informatics contribute without overstating what the data can tell us?
Studying how transparent methods, careful validation, clinical context, and explicit limitations can support responsible interpretation and more equitable applications.
Continue Exploring
Follow the learning, questions, and projects behind the direction
Read my developing reflections in The Informatics Diary, explore the technical and educational projects supporting this path, or connect with me about aligned academic, research, and professional opportunities.