Courses with Gaps

Definition of economics of health information, and marketing of health information, theories of national choice and utility applied to health information products/ services, demands and uses of health information products. Cost theory of health information models of value of health information products: exchange, use and expectation value, supply and demand functions of health information, marketing mix: price, product, place and promotion as applied to health information (products/ services), market aggregation and segmentation, consumer behavior. Health information life cycle development, market research, health information brokerage, writing proposal, marketing communication, costing and pricing methods.

Concepts and definition of terms in epidemiology. Purpose of epidemiology. Relationship in epidemiological triad. Epidemiological models and application. Epidemiological study designs and types. Application of epidemiology to communicable and non-communicable diseases. Measuring and interpreting patterns of disease occurrence. Routine sources of data. Communicable diseases (such as diseases of contact and droplets, water and food related,diseases spread by insects and other animals and many others) and their management. Non communicable diseases. HIV and sexually transmitted infections/diseases. Use of Integrated Disease Surveillance and Response (IDSR) Framework. -

Introduction to the fundamentals of nursing as a profession, rudiments of health attainment and health care, giving extensive considerations to the roles of nurses within organisational and professional ethical prescriptions for the practice of nursing. Interpersonal communication and understanding of scientific basis of nursing care. Laboratory demonstration of basic nursing skills prior to exposure to clinical practice.

Anatomy of flowering plants, primary vegetative body: stem, leaf and root to show the mature tissues namely parenchyma, collenchyma, sclerenchyma, xylem and phloem. Types of fruits and seeds. Care and use of dissecting kits and other biological wares. Dissection and general histology of animal tissues based on vertebrate forms. Morphology and functions of epithelial, muscular, nervous and connective tissues. Examination of various groups of lower invertebrates under microscopes, identification of various groups of organisms in Animal Kingdom. And any experiment designed to emphasise the practical aspects of topics in BIO 102.

Definition of health care, meaning of finance, sources and management of health care finance, define health insurance, purpose of health insurance scheme. Assumption of private health insurance. Comparison of private and government-sponsored health insurance. Analysis of diversity of voluntary medical care insurance plans under different sponsorships, scope of coverage and benefits of national health insurance scheme, analysis and critique of National Health Insurance scheme, examination of decree establishing the National Health Insurance Scheme.

The course is designed to acquaint students in the discipline of health sciences with management information and skills in matters relating to all aspects of the national health care systems and Policies, (the primary health care, the secondary health care and the tertiary health care systems). The course gives an overview of the national health policy and the development of the national health systems. Introduction to Nigeria Health care system. Definition of Health Economics and health care finance. Principles of demand and supply and their application to health care. How societies pay for health care services. Primary role of finance in Health care organisation, the four Cs, cost, cash, capital and control. Health Financing and different methods of Financing Health needs. Principles and practice of Health Insurance Scheme and challenges of the programme. Health Policy Management. National Health Care Agencies in Nigeria. Process of Health Budgeting Law making in State and Federal Government. Social Policies for vulnerable populations in Nigeria. Evaluation of Health care policies. Elements of financial management, health care settings, Government Hospitals, Private Hospital, Private no Profit Hospitals, other sources of health care like patent medical stores in village communities. Outpatient care, long term care and its cost implication. Regulations and Legal Issues in health care and its financing. Health care budget and financial challenges of the health care system.

The course is designed to acquaint students in the discipline of health sciences with management information and skills in matters relating to all aspects of the national health care systems, (the primary health care, the secondary health care and the tertiary health care systems). Students should learn organisational behaviour, theories of motivation and managerial skills. The course gives an overview of the national health policy and the development of the national health systems. The roles of governments at each of the levels and those of the NGOs are highlighted. Modern concepts and elements of management by objectives are reviewed in the context of health planning, implementation and health programme monitoring and evaluation. Principles and practice of Health Insurance Scheme and challenges of the programme. Modalities for leading health team and organising health care activities are as well highlighted Methods and means of managing human and material resources are also covered. The course covers also various aspects of selected international health care system.

Mandatory 6 months uninterrupted SIWES training at the 300-level second semester. Work experience in public or private institutions and organisations relevant to the programme and or job market such as hospitals, nursing homes, ambulatory care facilities, physician practices, insurance organisations, health-related research and development firms, pharmaceutical and medical equipment companies.

Introduction to immune system: Definitions, types (adaptive and innate), B and T lymphocytes, chemical mediators (cytokines, interleukenes, antibodies, and many others). Abnormal immune responses: Hypersensitivity (Type I, II, III, IV), Autoimmunity, immunodeficiency diseases. Immunosuppressive drugs: Glucocorticoids, Calcineurin inhibitors, Anti-proliferatives (mycophenolate e.t.c), cytotoxic agents, Antibodies, RhO (D) immune globulin, Monoclonal antibodies, (rituximab and many others). Cytokines: Interferones, TNF – alpha, and many others. Drug allergy, Tumor markers for solid tumors. Antigraft rejection drugs. Steroidal and non- steroidal anti-inflammatory drugs. Used in the treatment of gout. Practical: Designed to reflect experimental models of the topics taught above.

This is an introductory course on Artificial Intelligence. The topics include; Overview: foundations, scope, problems, and approaches of AI. Intelligent agents: reactive, deliberative, goal-driven, utility-driven, and learning agents; Artificial Intelligence programming techniques. Problem-solving through Search: forward and backward, state-space, blind, heuristic, problem-reduction, A, A*, AO*, minimax, constraint propagation, neural, stochastic, and evolutionary search algorithms, sample applications. Knowledge Representation and Reasoning: ontologies, foundations of knowledge representation and reasoning, representing and reasoning about objects, relations, events, actions, time, and space; predicate logic, situation calculus, Content logics, reasoning with defaults, reasoning about knowledge, sample applications. Planning: planning as search, partial order planning, construction and use of planning graphs. Representing and Reasoning with Uncertain Knowledge: probability, connection to logic, independence, Bayes rule, bayesian networks, probabilistic inference, sample applications. Decision-Making: basics of utility theory, decision theory, sequential decision problems, elementary game theory, sample applications. Machine Learning and Knowledge Acquisition: learning from memorisation, examples, explanation, and exploration. learning nearest neighbor, naive Bayes, and decision tree classifiers, Q-learning for learning action policies, applications. Sample Applications of AI, student project presentations.