Please use this identifier to cite or link to this item: https://hdl.handle.net/2440/9953
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Type: Journal article
Title: Automated attention flags in chronic disease care planning
Author: Warren, J.
Noone, J.
Smith, B.
Ruffin, R.
Frith, P.
Van Der Zwaag, B.
Beilakov, G.
Frankel, H.
McElroy, H.
Citation: Medical Journal of Australia, 2001; 175(17 September 2001):308-312
Publisher: Australasian Med Publ Co Ltd
Issue Date: 2001
ISSN: 0025-729X
1326-5377
Statement of
Responsibility: 
J.R. Warren, J.T. Noone, B.J. Smith, R. Ruffin, P. Frith, B.J. van der Zwaag, G.V. Beliakov, H.K. Frankel and H.J. McElroy
Abstract: OBJECTIVES: To assess the value of computerised decision support in the management of chronic respiratory disease by comparing agreement between three respiratory specialists, general practitioners (care coordinators), and decision support software. METHODS: Care guidelines for two chronic obstructive pulmonary disease projects of the SA HealthPlus Coordinated Care Trial were formulated. Decision support software, Care Plan On-Line (CPOL), was created to represent the intent of these guidelines via automated attention flags to appear in patients' electronic medical records. For a random sample of 20 patients with care plans, decisions about the use of nine additional services (eg, smoking cessation, pneumococcal vaccination) were compared between the respiratory specialists, the patients' GPs and the CPOL attention flags. RESULTS: Agreement among the specialists was at the lower end of moderate (intraclass correlation coefficient [ICC], 0.48; 95% CI, 0.39-0.56), with a 20% rate of contradictory decisions. Agreement with recommendations of specialists was moderate to poor for GPs (kappa, 0.49; 95% CI, 0.33-0.66) and moderate to good for CPOL (kappa, 0.72; 95% CI, 0.55-0.90). CPOL agreement with GPs was moderate to poor (kappa, 0.41; 95% CI, 0.24-0.58). GPs were less likely than specialists or CPOL to decide in favour of an additional service (P<0.001). CPOL was 87% accurate as an indicator of specialist decisions. It gave a 16% false-positive rate according to specialist decisions, and flagged 61% of decisions where GPs said No and specialists said Yes. CONCLUSIONS: Automated decision support may provide GPs with improved access to the intent of guidelines; however, further investigation is required.
Keywords: Humans
Lung Diseases, Obstructive
Medical Records Systems, Computerized
Reminder Systems
Software
Decision Support Systems, Clinical
Patient Care Planning
South Australia
Practice Guidelines as Topic
Description: © Australasian Medical Publishing
DOI: 10.5694/j.1326-5377.2001.tb143588.x
Published version: http://dx.doi.org/10.5694/j.1326-5377.2001.tb143588.x
Appears in Collections:Aurora harvest 4
Medicine publications

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