Lecture: 4 hours/week
Lab: 1.5 hours/week
Practicum: 4 hours/week
or
Hybrid: 2 hours/week in class
2 hours/week online
Lab: 1.5 hours/week
Practicum: 4 hours/week
In this course, students engage in a variety of learning activities such as lectures, case study analysis, independent research, exercises, training on data classification technology, participant presentations, classroom discussions and guest speakers.
- The essentials of data classification including coding processes, principles, structure and guidelines pertaining to ICD and CCI.
- The information and processes relevant to specified Major Clinical Categories.
- The application of the coding process and guidelines to assign appropriate diagnosis and intervention codes to major clinical categories.
- Application of case mix and resource intensity weight methodologies.
At the end of the course, the successful student will be able to:
- apply knowledge of medical terminology, anatomy and pathophysiology to determine etiology;
- analyze case studies to determine principle diagnoses, interventions, complications and comorbidities;
- assess and apply international and national coding and documentation standards;
- navigate ICD, CCI, data abstracting systems and electronic health records to complete the classification process;
- discover the importance of data integrity;
- apply case mix and resource intensity weight methodologies.
The course evaluation is consistent with the ÁñÁ«ÊÓƵ Evaluation Policy. An evaluation schedule is presented at the beginning of the course. This is a graded course. All assignments must be completed to pass the course.
A list of required and optional textbooks, materials and electronic applications is provided for students at the beginning of each semester.
Students in the BScHIM program are required to maintain a passing grade of 65% (C+) in all courses in order to progress in the program.