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The Master of Science with a concentration in healthcare analytics at Lamar University is a compact, 30-hour graduate program designed to bridge clinical knowledge and computational skill sets. This curriculum is offered both on-campus and online, making it accessible to working professionals and students who prefer a campus experience. The program teaches how to locate and combine diverse healthcare data sources, perform rigorous data cleaning, and construct analytics workflows that inform operational and clinical decisions. Students also learn to assess the broader implications of analytics in health systems, ranging from cost and access questions to patient safety and regulatory compliance.
This degree is built for two overlapping audiences: practitioners from the health sector who want to move into analytics, and technologists who want to apply their skills to healthcare problems. The curriculum emphasizes practical competencies such as data acquisition, data management, and predictive modeling, alongside an understanding of healthcare delivery and policy. Graduates leave with the ability to propose and implement analytics solutions that aim to improve outcomes, reduce inefficiencies, and support decision-makers. The program maintains a balance between technical training and applied health industry knowledge to ensure relevance in real-world settings.
Curriculum and learning outcomes
The coursework is organized to develop analytic fluency and industry insight. Core components teach students to extract, transform, and load data from electronic health records, claims, devices, and other repositories. Learners practice building models that forecast patient risk, utilization, and outcomes using machine learning and statistical methods. They also learn to design evaluation strategies that test hypotheses and measure impact. A critical part of the curriculum is examining the ethical and operational consequences of analytics choices, ensuring students can weigh benefits against privacy and equity concerns.
Technical competencies
Students gain hands-on experience with tools and processes central to healthcare analytics. Instruction covers data acquisition methods for heterogeneous sources, techniques for data cleaning and normalization, and the application of predictive modeling for clinical and administrative use cases. Coursework emphasizes reproducible workflows and interpretable models so that results can be validated and communicated to clinical teams. Through projects, learners apply algorithms to realistic datasets and learn to translate technical outputs into actionable recommendations.
Policy, ethics, and system impacts
Beyond algorithms, the program addresses system-level questions about how analytics reshape care delivery. Students explore differing payment models, access issues, and value-based care debates to understand the environment where analytics will be implemented. The curriculum also engages with legal and regulatory frameworks that govern data use and teaches students how to construct compliance-oriented plans such as incident response plans and continuity plans. This prepares graduates to anticipate risks and design safeguards for sensitive health information.
Course highlights
A selection of courses illustrates the program’s mix of technical and sectoral learning. A course in healthcare economics introduces students to the distinct economic dynamics of health services, clarifying why healthcare markets differ from other industries and how that affects payment strategies and business viability. Another course on healthcare entrepreneurship surveys the roles of providers, payers, and industry actors—covering managed care, hospital operations, physician practice models, and commercial healthcare ventures—so analytics work aligns with organizational realities.
The program also includes a course on healthcare strategy that frames debates about the nature of healthcare as a public good versus a commodity. Students debate models such as fee-for-service, managed care, private insurance, and single-payer approaches while learning to evaluate outcomes and patient-perceived value. A dedicated course on healthcare analytics and AI focuses on how artificial intelligence and advanced analytics support clinical decision-making and operational optimization. Finally, a course in cybersecurity management trains students to identify threats, assess vulnerabilities, and prepare business impact analyses and recovery plans, equipping them for leadership roles in protecting healthcare data.
Career pathways and competencies
Graduates are prepared for roles such as clinical data analyst, healthcare data scientist, analytics manager, and informatics specialist. Beyond technical chops, the program fosters skills in communicating results to clinicians and administrators, designing ethically informed interventions, and aligning analytics work with organizational strategy. With training that spans data science, healthcare systems, and cybersecurity, alumni are qualified to help health organizations harness data to improve patient outcomes and operational performance while safeguarding privacy and compliance.