Description: This course will introduce students to machine learning and other big data analytic techniques. We will illustrate the strengths and limitations of these tools and their applications for policy and industry. Topics will include risk prediction, precision medicine, and population health. We will also discuss the legal and ethical issues.
Course Goals: Introduce machine learning techniques. Understand their strengths and limitations. Understand relationship between these tools and concepts such as population health and precision medicine. Ability to apply tools to health institutions and policies. Awareness of potential unintended consequences of these tools.
Competencies: a. A.1 Identify appropriate sources and gather information, effectively and efficiently
b. A.2 Appraise literature and data critically
c. A.3 Develop, understand and use data from performance, surveillance or monitoring systems
d. A.5 Statistical analysis
e. A.7 Economic analysis: Use basic microeconomic theory to understand how the incentives of consumers, providers, and payers affect behaviors, costs, and other outcomes; understand and apply basic econometric tools for the empirical study of issues in health economics.
f. A.8 Operational analysis: Analyze, design, or improve an organizational process, including the use of quality management, process improvement, marketing and information technology principles and tools.
g. A.9 Population health assessment: Understand and apply basic epidemiologic principles, measures, and methods to assess the health status of a population; identify risk factors in individuals and communities; evaluate the impact of population-based interventions and initiatives.
h. A.10 Decision Making: Implement a decision-making process that incorporates evidence from a broad analysis that includes uncertainty, risk, stakeholders, and organizational values.
i. B.1 Convey: Speak and write in a clear, logical, and grammatical manner in formal and informal situations; prepare cogent business presentations; facilitate an effective group process.
j. C.1 Organizational Vision: Through effective governance, establish an organization's values, vision, and mission; systematically enhance performance and human, material and knowledge resources.
k. C.2 Strategic Orientation: Analyze the business, demographic, ethno-cultural, political, and regulatory implications of decisions and develop strategies that continually improve the long-term success and viability of the organization.
l. C.5 Collaboration: Work collaboratively with others as part of a team or group, demonstrating commitment to the team's goal and encouraging individuals to put forth their best effort.
m. C.7 Organizational Awareness: Understand and learn from governance structures, formal and informal decision-making structures, and power relationships in an organization, industry, or community.
n. D.2 Behave ethically and promote standards of ethical behavior throughout organizations and professional communities.
o. E.3 Continuously push self to raise personal standards of performance and exceed expectations.
3. Analyze quantitative and qualitative data using biostatistics, informatics, computer-based programming and software, as appropriate
4. Interpret results of data analysis for public health research, policy or practice
7. Assess population needs, assets and capacities that affect communities' health
15. Evaluate policies for their impact on public health and health equity
19. Communicate audience-appropriate public health content, both in writing and through oral presentation
21. Perform effectively on interprofessional teams
Learning Objectives: 3. Explain the role of quantitative and qualitative methods and sciences in describing and assessing a population's health.
10. Explain the social, political and economic determinants of health and how they contribute to population health and health inequities.