Mass Medication Clinic (MMC) Patient Medical Assistant (PMA) System Training Initiative

Abstract

In a disease outbreak medication needs to be rapidly yet safely distributed to a population to minimize infection outbreak. We investigated if there are significant differences in efficiency (time) and error rates in drug dissemination to large groups of people using algorithm driven paper vs. PDA methodology. Subjects were sent through points of dispensing with volunteer clerks processing them during two sessions (alternating modes for session two). Time to process subjects through each arm was recorded, along with the errors in medication prescription. Data analysis indicated no significant difference in time or number of errors made with PDA vs. paper methods. However, the mode and order of testing affected time. Clerks doing the paper method second were slower than those who did paper first (P = 0.001). The PDA method was consistent in time whether clerks used it first or second. This may indicate the presence of a fatigue factor from using the paper method. Both methods require questions to be asked, but the PDA requires less thinking as one only plugs in answers to questions, whereas the clerks using paper must also interpret the answer and follow the paper-based algorithm. This may have resulted in slower times as fatigue played a role in the second session. The findings may indicate that during a disease outbreak, when clerks are tired yet still must continue processing citizens, an algorithm-driven PDA may be beneficial to improve efficiency.

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Document Details

Document Type
Technical Report
Publication Date
Jun 01, 2007
Accession Number
ADA476406

Entities

People

  • Lawrence Burgess
  • R. D. Clyde
  • Victoria Garshnek

Tags

Communities of Interest

  • Biomedical

DTIC Thesaurus Topics

  • Algorithms
  • Computer Programming
  • Computers
  • Data Analysis
  • Data Transmission
  • Databases
  • Disease Outbreaks
  • Diseases And Disorders
  • Electronic Mail
  • Health
  • Health Care
  • Health Services
  • Medical Personnel
  • Mobile Devices
  • Personal Digital Assistants
  • Public Health
  • Statistical Analysis

Readers

  • Brain and Cognitive Science; Experimental Psychology; Cognitive Neuroscience
  • Computer Science/Computer Engineering/Data Science/Digital Signal Processing.
  • Medical or Health Care Field.