MED 293 — الإحصاء الحيوي والمعلوماتية الصحية
السنة 2 · 16 محاضرة · 3 ساعة معتمدة
العناوين والأهداف منقولة من خطة كلية الطب الرسمية.
1. Population and Samples, Sampling Techniques, Data types and Data Sources
Biostatistics
- Understand the different types of data, their resources and their quality.
- Describe different types of data, their resources and their quality and understand collection and flow of health data.
2. Descriptive statistics: Measures of central tendency and measures of variability
Biostatistics
- Develop measures that can be used to summarize a data set: mean, median, mode, percentiles, variance, standard deviation, and range.
- Develop measures that can be used to indicate the amount of variation in the data set: percentiles, variance, standard deviation, and range.
- Know what it means for a data set to be normal.
- Discuss a measure of the degree to which a scatter diagram of paired values can be approximated by a straight line.
- Discuss the empirical rule.
3. Probability
Biostatistics
- Understand the concept of the probability of an event.
- Understand the properties of probabilities.
- Understand the application of probabilities in assessment of screening tests and diagnostic tests.
4. Normal Distribution
Biostatistics
- Understand continuous random variables.
- Understand normal distribution.
- Understand standard normal distribution.
- Understand the percentiles of a normal random variables.
- Know how to convert normal distribution to standard normal distribution.
5. Sampling Distribution
Biostatistics
- Understand the concept of sampling from a population distribution.
- Know the distribution (mean and variance) of the sample mean, proportion, difference between two sample means, and difference between two sample proportions.
- Know the central limit theorem and its application in biological fields.
6. Estimation of population parameters (mean, proportion, difference between two means, and difference between two proportions)
Biostatistics
- Know how to use sample data to estimate a population mean, a population variance, and a population proportion.
- Know how to compute point and interval estimates of the population parameters.
7. Hypothesis testing: Introduction
Biostatistics
- Understand a statistical hypothesis and know how to use sample data to test it.
- Understand the difference between the null and the alternative hypothesis.
- Understand the significance of a rejecting a null hypothesis or not rejecting it.
- Understand the meaning of level of significance and p value.
8. Hypothesis testing: One-sample test / Two-sample test (independent samples)
Biostatistics
- Know how to test for population mean when population standard deviation is known.
- Know how to test for population mean when population standard deviation is unknown.
- Understand the importance of using a control in the testing of a new drug or a new procedure.
- Know how to test the equality of two population means when the population variances are known.
- Know how to test the equality of two population means when the population variances are unknown but assumed equal.
- Know how to test the equality of two population means when the population variances are unknown but assumed unequal.
- Know how to test the two-sample hypothesis using confidence interval approach.
9. Informatics in health care professions
Health Informatics
- Introduction to Information, Information Science and Information Systems.
- Competencies and Skills.
- Understand the definitions of the terms used throughout the material, including Medical Information Systems itself.
- Recognize the role of Medical Information Systems in health care sectors, and the roles of Medical Information Systems in business.
10. Electronic health records (EHRs); Health information exchange (HIE); Components of Informatics Practice; The Informatics Team
Health Informatics
- Electronic health records (EHRs).
- Health information exchange (HIE).
- Components of Informatics Practice.
- The Informatics Team.
- The roles of Health Informaticians.
- Understand the value of electronic health records data in clinical research.
- Understand electronic health records as a data source, data quality, data elements in electronic health records.
11. Sub-specialties of the informatics
Health Informatics
- Understand different types of Medical Information Systems used in the health care sectors.
- Sub-specialties listed: clinical informatics, imaging informatics, bioinformatics, public health informatics, nursing informatics, pharmacy informatics, clinical research informatics.
- Consumer health informatics.
12. Medical information systems
Health Informatics
- Clinical information system.
- Nursing information system.
- Radiology information systems.
- Laboratory information systems.
- Pharmacy information systems.
- Describe the main types of commercial HIS software.
13. Electronic Health Records Implementation, Big Data, Sensor Informatics, Mobile Health, Social Health
Health Informatics
- Electronic Health Records Implementation.
- Big Data.
- Sensor Informatics.
- Mobile Health.
- Social Health.
- Health Data Challenges.
- Big data analysis.
- Understand the challenges in the analysis of data from electronic health records.
14. Secondary Analysis of Electronic Health Record
Health Informatics
- Introduce students to the EHR and their use.
- Demonstrate knowledge of the development of EHR.
- Describe the fundamental components and processes of health information systems.
- Apply confidentiality and security measures to protect electronic health information.
15. Current Trends and Emerging Technologies
Health Informatics
- Current Trends and Emerging Technologies.
- Digital Health Services.
- Telehealth/Telemedicine.
- Patient Privacy and Security.
- EHRs and Documentation.
- Artificial Intelligence (AI).
16. Evaluation Research in Health Informatics
Health Informatics
- Evaluation Research in Health Informatics.
- What is the research?
- Types of research.
- Global health informatics.
- Designs of research and their applications in health informatics.