Automated attention flags in chronic disease care planning

J.R. Warren, J.T. Noone, B.J. Smith, R. Ruffin, P. Frith, B.J. van der Zwaag, G.V. Beliakov, H.K. Frankel, H.J. McElroy

    Research output: Contribution to journalArticleAcademicpeer-review

    11 Citations (Scopus)

    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.
    Original languageUndefined
    Pages (from-to)308-312
    Number of pages5
    JournalMedical journal of Australia
    Volume175
    Issue number6
    Publication statusPublished - Sep 2001

    Keywords

    • EWI-1439

    Cite this

    Warren, J. R., Noone, J. T., Smith, B. J., Ruffin, R., Frith, P., van der Zwaag, B. J., ... McElroy, H. J. (2001). Automated attention flags in chronic disease care planning. Medical journal of Australia, 175(6), 308-312.
    Warren, J.R. ; Noone, J.T. ; Smith, B.J. ; Ruffin, R. ; Frith, P. ; van der Zwaag, B.J. ; Beliakov, G.V. ; Frankel, H.K. ; McElroy, H.J. / Automated attention flags in chronic disease care planning. In: Medical journal of Australia. 2001 ; Vol. 175, No. 6. pp. 308-312.
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    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.",
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    author = "J.R. Warren and J.T. Noone and B.J. Smith and R. Ruffin and P. Frith and {van der Zwaag}, B.J. and G.V. Beliakov and H.K. Frankel and H.J. McElroy",
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    Warren, JR, Noone, JT, Smith, BJ, Ruffin, R, Frith, P, van der Zwaag, BJ, Beliakov, GV, Frankel, HK & McElroy, HJ 2001, 'Automated attention flags in chronic disease care planning' Medical journal of Australia, vol. 175, no. 6, pp. 308-312.

    Automated attention flags in chronic disease care planning. / Warren, J.R.; Noone, J.T.; Smith, B.J.; Ruffin, R.; Frith, P.; van der Zwaag, B.J.; Beliakov, G.V.; Frankel, H.K.; McElroy, H.J.

    In: Medical journal of Australia, Vol. 175, No. 6, 09.2001, p. 308-312.

    Research output: Contribution to journalArticleAcademicpeer-review

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    T1 - Automated attention flags in chronic disease care planning

    AU - Warren, J.R.

    AU - Noone, J.T.

    AU - Smith, B.J.

    AU - Ruffin, R.

    AU - Frith, P.

    AU - van der Zwaag, B.J.

    AU - Beliakov, G.V.

    AU - Frankel, H.K.

    AU - McElroy, H.J.

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    N2 - 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.

    AB - 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.

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    Warren JR, Noone JT, Smith BJ, Ruffin R, Frith P, van der Zwaag BJ et al. Automated attention flags in chronic disease care planning. Medical journal of Australia. 2001 Sep;175(6):308-312.