| Title | Automated Dose-Rounding Recommendations for Pediatric Medications |
| Author(s) | Kevin B. Johnson, MD, MS, Carlton K. K. Lee, PharmD, MPH, S. Andrew Spooner, MD, MSc, Coda L. Davison, MPA, BBA, Jill S. Helmke, DPh, NPh, Stuart T. Weinberg, MD |
| Source | Pediatrics, Vol. 128, No. 2, Pages 422-428 |
| Publication Date | 1-Aug-11 |
| Abstract | BACKGROUND: Although pediatric electronic prescribing systems are increasingly being used in pediatric care, many of these systems lack the clinical decision-support infrastructure needed to calculate a safe and effective rounded medication dose. This infrastructure is required to facilitate tailoring of established dosing guidance while maintaining the medication's therapeutic intent. OBJECTIVE: The goal of this project was to establish best practices for generating an appropriate medication dose and to create an interoperable rounding knowledge base combining best practices and dose-rounding information. METHODS: We interviewed 19 pediatric health care and pediatric pharmacy experts and conducted a literature review. After using these data to construct initial rounding tolerances, we used a Delphi process to achieve consensus about the rounding tolerance for each commonly prescribed medication. RESULTS: Three categories for medication-rounding philosophy emerged from our literature review: (1) medications for which rounding is used judiciously to retain the intended effect; (2) medications that are rounded with attention to potential unintended effects; and (3) medications that are rarely rounded because of the potential for toxicity. We assigned a small subset of medications to a fourth category -- inadequate data -- for which there was insufficient information to provide rounding recommendations. For all 102 medications, we were able to arrive at a consensus recommendation for rounding a given calculated dose. CONCLUSIONS: Results of this study provide the pediatric information technology community with a primary set of recommended rounding tolerances for commonly prescribed drugs. The interoperable knowledge base developed here can be integrated with existing and developing electronic prescribing systems, potentially improving prescribing safety and reducing cognitive workload. |