Twenty-five years bridging clinical operations, health information technology, and audit-grade data analytics — helping health systems, payers, and higher education institutions turn evidence into better outcomes.
Dr. Charlyn A. Hilliman
Dr. Charlyn A. Hilliman is a healthcare executive and the founder of ETHill Consulting, LLC, bringing more than 25 years of experience across clinical operations, health information technology, and data analytics.
Her expertise spans EHR optimization, NIST-based cybersecurity risk assessment, enterprise systems integration, and cloud/SaaS architecture, paired with hands-on fluency in Python, R, SQL, SPSS, SAS, and JASP for predictive modeling, continuous auditing, and data governance. She has led large-scale enterprise technology migrations, built AI-enabled early-alert and continuous-monitoring systems, and designed enterprise data governance frameworks used across healthcare and higher education settings — serving populations of 40,000+ at institutional scale.
She also brings deep experience in higher education program design — developing and teaching graduate curricula in quantitative methods, program evaluation, and AI governance, and leading AI-infused curriculum development that helps academic programs teach emerging technology responsibly. A published scholar in health informatics and data governance, Dr. Hilliman pairs technical depth with the strategic judgment to align data, technology, and curriculum decisions with organizational mission. She is a Certified Diversity Executive (CDE®), an alumna of the McKinsey Black Executives Leadership Program, and a United States Air Force veteran.
Today, Dr. Hilliman leads ETHill Consulting's advisory practice in clinical operations, health IT, and audit analytics — work grounded as much in direct operating, hands-on care delivery experience as in research and strategy.
ETHill Consulting brings together the capabilities healthcare and higher-education organizations most often try to buy separately — clinical operating expertise, health IT leadership, rigorous data and audit analytics, and academic program design.
Home health and ambulatory operations, regulatory compliance (HIPAA, state and federal home-care standards), quality improvement, and care-model design — grounded in direct operating experience, not just theory.
EHR optimization, NIST-based cybersecurity risk assessment, enterprise systems integration (Workday, Salesforce, JD Edwards), cloud/SaaS architecture, and IT governance for hospitals, academic medical centers, and universities.
SOX and continuous-auditing frameworks, predictive analytics with logistic regression and classification modeling (Python, R, SQL, SPSS, SAS, JASP), enterprise data governance, and responsible AI governance advisory.
Curriculum development and redesign — including AI-infused curriculum design — faculty hiring and evaluation rubrics, instructional technology integration, and HLC accreditation readiness for graduate and undergraduate programs.
Executive coaching and leadership development for senior leaders across healthcare, education, and nonprofit sectors — paired with DEI program architecture from a Certified Diversity Executive and McKinsey Black Executives Leadership Program alumna. Engagements have included diversity data-analysis frameworks, standardized hiring rubrics that cut hiring timelines by 30%, and enterprise-wide DEI strategy design.
A sample of the frameworks and models built across higher education, healthcare, and consulting engagements — shown the way they'd appear on a dashboard.
Logistic regression model flagging at-risk learners across 40,000+ online students — enabling proactive advising before withdrawal.
Impact × Likelihood risk scoring (1–25) used to prioritize control-domain audit coverage in real engagements.
Enterprise data stewardship frameworks built for hospital systems, universities, and academic-medical-center consulting clients.
Six-stage methodology testing full control populations — not samples — across enterprise data sources.
Graduate and undergraduate course design across quantitative methods, program evaluation, and applied AI governance — translating emerging technology into teachable, accreditation-ready curricula.
The first two weeks after discharge do not have to be the most dangerous two weeks in a patient's care — with the right model in place, they can be the most supported.— Dr. Charlyn A. Hilliman, "The Most Dangerous Two Weeks in Healthcare"
Preventable hospital readmissions concentrate in the first 7–14 days after discharge — a window shaped by deconditioning, medication complexity, and home hazards that claims data rarely captures. This white paper proposes a wearable-enabled, closed-loop home care model and lays out the payer economics behind it.
There is a window of time after a hospital discharge that the healthcare system has never fully figured out how to close — and the consequences are measured in readmissions, ED visits, and in some cases, lives. Dr. Hilliman unpacks why the first two weeks at home remain so dangerous, and what a disciplined, closed-loop model of care could change.
