A computerised prescribing decision support system to improve patient adherence with prescribing: A randomised controlled trial

John W Bennett, Paul P Glasziou, Chris Del Mar, Frederick De Looze

Research output: Contribution to journalArticleResearchpeer-review

9 Citations (Scopus)

Abstract

BACKGROUND Medication adherence is often suboptimal and this leads to poorer health outcomes.
METHODS Participants: 179 adult patients taking three or more, long term medications in one academic general practice
in Brisbane, Queensland.
Design: Unblinded, factorial, randomised controlled trial of computer generated consumer product information,
computer generated medication timetable, both, or usual care.
Main outcome measures: We derived adherence to medication by measuring the relative prescription rate for six groups
of medications extracted by the Health Insurance Commission. We also measured patients' knowledge of, and
satisfaction with, medications, and general practitioners' attitudes to the decision support system.
RESULTS There was no effect on medication adherence. Although GPs were supportive of the system, neither patients'
self reported knowledge of medications, nor satisfaction with care, was increased by the intervention.
CONCLUSION Simply providing patients with medication timetables and computer generated consumer product
information does not improve drug adherence in primary care
Original languageEnglish
Pages (from-to)667-671
Number of pages5
JournalAustralian Family Physician
Volume32
Issue number8
Publication statusPublished - 2003
Externally publishedYes

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Patient Compliance
Medication Adherence
Randomized Controlled Trials
Queensland
Health Insurance
General Practitioners
Prescriptions
Primary Health Care
Outcome Assessment (Health Care)
Health
Pharmaceutical Preparations

Cite this

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title = "A computerised prescribing decision support system to improve patient adherence with prescribing: A randomised controlled trial",
abstract = "BACKGROUND Medication adherence is often suboptimal and this leads to poorer health outcomes.METHODS Participants: 179 adult patients taking three or more, long term medications in one academic general practicein Brisbane, Queensland.Design: Unblinded, factorial, randomised controlled trial of computer generated consumer product information,computer generated medication timetable, both, or usual care.Main outcome measures: We derived adherence to medication by measuring the relative prescription rate for six groupsof medications extracted by the Health Insurance Commission. We also measured patients' knowledge of, andsatisfaction with, medications, and general practitioners' attitudes to the decision support system.RESULTS There was no effect on medication adherence. Although GPs were supportive of the system, neither patients'self reported knowledge of medications, nor satisfaction with care, was increased by the intervention.CONCLUSION Simply providing patients with medication timetables and computer generated consumer productinformation does not improve drug adherence in primary care",
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A computerised prescribing decision support system to improve patient adherence with prescribing : A randomised controlled trial. / Bennett, John W; Glasziou, Paul P; Del Mar, Chris; De Looze, Frederick .

In: Australian Family Physician, Vol. 32, No. 8, 2003, p. 667-671.

Research output: Contribution to journalArticleResearchpeer-review

TY - JOUR

T1 - A computerised prescribing decision support system to improve patient adherence with prescribing

T2 - A randomised controlled trial

AU - Bennett, John W

AU - Glasziou, Paul P

AU - Del Mar, Chris

AU - De Looze, Frederick

PY - 2003

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N2 - BACKGROUND Medication adherence is often suboptimal and this leads to poorer health outcomes.METHODS Participants: 179 adult patients taking three or more, long term medications in one academic general practicein Brisbane, Queensland.Design: Unblinded, factorial, randomised controlled trial of computer generated consumer product information,computer generated medication timetable, both, or usual care.Main outcome measures: We derived adherence to medication by measuring the relative prescription rate for six groupsof medications extracted by the Health Insurance Commission. We also measured patients' knowledge of, andsatisfaction with, medications, and general practitioners' attitudes to the decision support system.RESULTS There was no effect on medication adherence. Although GPs were supportive of the system, neither patients'self reported knowledge of medications, nor satisfaction with care, was increased by the intervention.CONCLUSION Simply providing patients with medication timetables and computer generated consumer productinformation does not improve drug adherence in primary care

AB - BACKGROUND Medication adherence is often suboptimal and this leads to poorer health outcomes.METHODS Participants: 179 adult patients taking three or more, long term medications in one academic general practicein Brisbane, Queensland.Design: Unblinded, factorial, randomised controlled trial of computer generated consumer product information,computer generated medication timetable, both, or usual care.Main outcome measures: We derived adherence to medication by measuring the relative prescription rate for six groupsof medications extracted by the Health Insurance Commission. We also measured patients' knowledge of, andsatisfaction with, medications, and general practitioners' attitudes to the decision support system.RESULTS There was no effect on medication adherence. Although GPs were supportive of the system, neither patients'self reported knowledge of medications, nor satisfaction with care, was increased by the intervention.CONCLUSION Simply providing patients with medication timetables and computer generated consumer productinformation does not improve drug adherence in primary care

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JF - Australian Family Physician

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