The importance of active learning and practice on the students' mastery of pharmacokinetic calculations for the intermittent intravenous infusion dosing of antibiotics

Abstract

Background: Estimation of pharmacokinetic parameters after intermittent intravenous infusion (III) of antibiotics, such as aminoglycosides or vancomycin, has traditionally been a difficult subject for students in clinical pharmacology or pharmacokinetic courses. Additionally, samples taken at different intervals during repeated dose therapy require manipulation of sampling times before accurate calculation of the patient-specific pharmacokinetic parameters. The main goal of this study was to evaluate the effectiveness of active learning tools and practice opportunities on the ability of students to estimate pharmacokinetic parameters from the plasma samples obtained at different intervals following intermittent intravenous infusion.

Methods: An extensive reading note, with examples, and a problem case, based on a patient's chart data, were created and made available to students before the class session. Students were required to work through the case before attending the class. The class session was devoted to the discussion of the case requiring active participation of the students using a random participation program. After the class, students were given additional opportunities to practice the calculations, using online modules developed by the instructor, before submitting an online assignment.

Results: The performance of students significantly (P < 0.001) improved from a baseline of 11.3% (pretest) to 60.3% (posttest) after the class discussion. The grades of students further improved (P < 0.001) to 89.3% on the take-home assignment after they had a chance to study on their own and work on the online practices. Finally, students scored 82.6% in a formal mid-term examination, suggesting significant retention of the materials.

Conclusions: Despite being a difficult subject, students achieve mastery of pharmacokinetic calculations for the topic of intermittent intravenous infusion when appropriate active learning strategies and practice opportunities are employed.

Figure 1

Plasma/serum concentration-time profiles of a drug administered by intermittent intravenous infusion or intravenous bolus method. Solid and dashed lines represent the intermittent intravenous infusion and intravenous bolus methods, respectively. Abbreviations: C_o = maximum concentration after the bolus dose; C_max = maximum concentration after the short infusion; t_inf = length of short infusion; C_min = minimum concentration.

Figure 2

Chart data. Excerpts from a patient’s chart data containing the medication administration record and laboratory (plasma concentration-time) data after administration of multiple doses of gentamicin to a patient (A) and manipulation of sampling time of trough or peak or calculation of sampling time within the interval for use in equation (1) (B).

Figure 3

Serum/plasma concentration-time Profiles. Serum/plasma concentration-time course of gentamicin after intermittent intravenous infusion in a patient after intravenous infusion of 80 mg of the drug over 30 min every 8 h, demonstrating the manipulation of peak or trough time (A) and calculation of sampling time for peak (T_peak) and trough (T_trough) within the interval (B). Solid triangles: peak and trough after the first dose; solid circles: peak and trough at steady state; dotted open circles: transposed peak or trough at steady state.

Figure 4

Performance data for the entire assessments. Grades of students in Pretest, Posttest, Assignment, and Examination for the entire class (n = 126) (A) and Abilene (n = 34) and Amarillo (n = 92) students separately (B). Columns and bars represent mean and SEM, respectively. *** P < 0.001.

Figure 5

Performance data for the individual questions. Percentages of students who answered each of the four questions correctly in Pretest, Posttest, Assignment, and Examination (n = 126). Abbreviations: k = elimination rate constant; C_max = maximum concentration; C_min = minimum concentration; V = volume of distribution.

Figure 6

Effects of online practice generation on the online assignment grade. Grades of students in the online assignment as a function of the number of online practices generated before the submission of the assignment. The percentages of students who generated zero, one, two, or three practices were 11.9%, 55.5%, 19.0%, and 7.1%, respectively. Symbols and bars represent mean and SEM, respectively.