Quality care for children: inpatient medication use in a mid-Atlantic hospital system 2000-2003

Tamar Lasky1, Stephen T Lawless, Jay Greenspan

  • 1College of Pharmacy, University of Rhode Island, Kingston, RI 02881, USA. tlasky@mail.uri.edu

Insights

This study analyzed pediatric inpatient medication use in over 32,000 hospitalizations from 2000-2003. Findings reveal medication probabilities vary by patient demographics, highlighting the need for further research in pediatric health services.

Area of Science:

  • Pediatric pharmacology
  • Health services research
  • Comparative effectiveness research

Background:

  • Electronic databases offer valuable insights into pediatric inpatient medication use.
  • Understanding medication patterns in children is crucial for optimizing healthcare delivery.
  • Previous analyses may not have encompassed the full pediatric age range (0-18 years).

Purpose of the Study:

  • To conduct a preliminary analysis of pediatric inpatient medication use.
  • To identify common medications administered to children across a defined geographic region.
  • To explore demographic variations in medication administration probabilities.

Main Methods:

  • Analysis of an electronic database comprising over 32,000 pediatric hospitalizations (2000-2003).
  • Inclusion of data from a specific catchment area serving Delaware, Maryland, New Jersey, and Pennsylvania.
  • Calculation of drug administration percentages for individual patients and identification of frequently used medications.

Main Results:

  • Over 700 different drugs were administered to the pediatric study population.
  • Nine drugs were received by at least 10% of all patients.
  • Medication probabilities demonstrated variation based on patient age, sex, and race.

Conclusions:

  • The analyzed database is a valuable resource for pediatric health services and comparative effectiveness research.
  • Preliminary findings indicate demographic factors influence pediatric medication use.
  • Further research is necessary to fully quantify and understand these variations in medication probabilities.

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