HIM 2201 - Introduction to Statistics and Data Analysis
College of Health Sciences
Credit(s): 3
Contact Hours: 47
Contact Hours: 47
Effective Term Spring 2022 (600)
Requisites
Permission of the Program and
Prerequisite any college level MAC, MGF or STA course with a grade of C or better and
Pre- or Co-requisite HIM 1800 with a minimum grade of C and
(Admission to Healthcare Data Management (Certificate with Financial Aid Eligibility) (HCINF-CT) or
Admission to Health Information Technology (Associate in Science) (HIT-AS))
Prerequisite any college level MAC, MGF or STA course with a grade of C or better and
Pre- or Co-requisite HIM 1800 with a minimum grade of C and
(Admission to Healthcare Data Management (Certificate with Financial Aid Eligibility) (HCINF-CT) or
Admission to Health Information Technology (Associate in Science) (HIT-AS))
Course Description
This course addresses computation of rates and percentages for basic healthcare statistics with introduction to vital statistics, data display, report generation, and research methodologies.
Learning Outcomes and Objectives
- The student will identify common healthcare statistical terms and definitions by:
- defining common healthcare statistical terms and abbreviations.
- defining and computing mean, median & mode.
- recognizing the separate computation of newborn census figures.
- applying methods for determining the number of days in a period.
- assigning the appropriate service and disposition for discharged patients.
- defining, differentiating and applying the terms census, daily census, inpatient service day and total inpatient service days.
- defining and differentiating between the following terms: bed count and newborn bed count, bed count days and newborn bed count days.
- The student will formulate descriptive healthcare statistics to draw conclusions by:
- calculating fractions, percentages, percentiles, rations and conversions using healthcare formulas.
- computing daily census and inpatient service days using admission and discharge data provided.
- computing average daily census for a patient care unit given inpatient service days for any such unit.
- computing the bed occupancy ratio for any period given the data representing bed count and inpatient service days.
- computing the bassinet occupancy ratio for any period given bassinet count and newborn inpatient service days.
- computing the mortality, autopsy, length of stay, discharge days and bed turnover rates.
- The student will demonstrate the skills needed to accurately present data in verbal, written, and graphic forms by:
- processing and reporting census data and other statistical calculations.
- selecting the appropriate method for data presentation using tables, frequency, distribution and graphs.
- comparing and contrasting qualitative and quantitative research methods.
- The student will analyze various types of healthcare data by:
- identifying, defining, and applying the principles of quantitative and qualitative analysis.
- comparing and validating aggregate data.
- identifying various types and sources of data.
- The student will draw conclusions using quantitative analysis by:
- describing how health information management professionals create, use, gather, and analyze data in a systems context.
- using data analysis methods such as descriptive or inferential statistics.
- showcasing data to support decision making in a healthcare organization.
- The student will analyze external data to draw conclusions by:
- defining and using benchmarking to improve the quality of healthcare data.
- listing the benefits of benchmarking to an organization’s performance improvement.
- defining and constructing a dashboard report.
- describing best practices outlined by the National Committee for Quality Assurance (NCQA) organization.
- reporting the quality of care and services provided by the Healthcare Effectiveness Data and Information Set (HEDIS).
- The student will use the Tableau software program to appropriately demonstrate use of:
- acquiring data from online resources.
- utilizing basic descriptive, institutional, and healthcare statistics.
- analyzing data to identify trends.
- identifying potential abuse or fraudulent trends through data analysis.
- applying report generation technologies to facilitate decision making.
Criteria Performance Standard
Upon successful completion of the course the student will, with a minimum 78% percent accuracy, demonstrate mastery of each of the above stated objectives through classroom measures developed by individual instructors.
History of Changes
C&I Approval: 09/05/2019, BOT Approval: 09/24/2019, Effective Term: Spring 2020 (570).
C&I Approval: , BOT Approval: , Effective Term: Spring 2022 (600)
Related Programs
- Health Information Technology (HIT-AS) (640) (Active)
- Healthcare Data Management (HCINF-CT) (595) (Active)
