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  1. Article ; Online: Artificial intelligence clinical trials and critical appraisal: a necessity.

    Kovoor, Joshua G / Bacchi, Stephen / Gupta, Aashray K / O'Callaghan, Patrick G / Abou-Hamden, Amal / Maddern, Guy J

    ANZ journal of surgery

    2023  Volume 93, Issue 5, Page(s) 1141–1142

    MeSH term(s) Humans ; Artificial Intelligence ; Clinical Trials as Topic
    Language English
    Publishing date 2023-01-11
    Publishing country Australia
    Document type Journal Article
    ZDB-ID 2050749-5
    ISSN 1445-2197 ; 1445-1433 ; 0004-8682
    ISSN (online) 1445-2197
    ISSN 1445-1433 ; 0004-8682
    DOI 10.1111/ans.18263
    Database MEDical Literature Analysis and Retrieval System OnLINE

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    In stock of ZB MED Cologne/Königswinter

    Zs.A 180: Show issues Location:
    Je nach Verfügbarkeit (siehe Angabe bei Bestand)
    bis Jg. 1994: Bestellungen von Artikeln über das Online-Bestellformular
    Jg. 1995 - 2021: Lesesall (1.OG)
    ab Jg. 2022: Lesesaal (EG)

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  2. Article ; Online: Improving health care efficiency one click at a time.

    Bacchi, Stephen / Kovoor, Joshua / Gupta, Aashray / Tan, Sheryn / Sherbon, Tony / Bersten, Andrew / O'Callaghan, Patrick G / Chan, Weng O

    Internal medicine journal

    2023  Volume 53, Issue 7, Page(s) 1261–1264

    Abstract: Computers are an integral component of modern hospitals. Mouse clicks are currently inherent to this use of computers. However, mouse clicks are not instantaneous. These clicks may be associated with significant costs. Estimated costs associated with 10 ... ...

    Abstract Computers are an integral component of modern hospitals. Mouse clicks are currently inherent to this use of computers. However, mouse clicks are not instantaneous. These clicks may be associated with significant costs. Estimated costs associated with 10 additional clicks per day for 20 000 staff exceed AU$500 000 annually. Workflow modifications that increase clicks should weigh the potential benefits of such changes against these costs. Future investigation of strategies to reduce low-value clicks may provide an avenue for health care savings.
    MeSH term(s) Humans ; Time Factors ; Delivery of Health Care ; Computers ; Workflow
    Language English
    Publishing date 2023-07-04
    Publishing country Australia
    Document type Journal Article
    ZDB-ID 2045436-3
    ISSN 1445-5994 ; 1444-0903
    ISSN (online) 1445-5994
    ISSN 1444-0903
    DOI 10.1111/imj.16160
    Database MEDical Literature Analysis and Retrieval System OnLINE

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    In stock of ZB MED Cologne/Königswinter

    Zs.A 792: Show issues Location:
    Je nach Verfügbarkeit (siehe Angabe bei Bestand)
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    Zs.MO 424: Show issues

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  3. Article ; Online: How will the artificial intelligence algorithm work within the constraints of this healthcare system?

    Stretton, Brandon / Koovor, Joshua G / Hains, Lewis / Kleinig, Oliver / Tan, Sheryn / Gupta, Aashray K / Ittimani, Mana / Dwyer, Andrew / McNeil, Keith / Chan, WengOnn / Cusack, Michael / O'Callaghan, Patrick G / Maddison, John / Bacchi, Stephen

    Internal medicine journal

    2024  Volume 54, Issue 1, Page(s) 190–191

    MeSH term(s) Humans ; Artificial Intelligence ; Algorithms ; Delivery of Health Care
    Language English
    Publishing date 2024-01-24
    Publishing country Australia
    Document type Letter
    ZDB-ID 2045436-3
    ISSN 1445-5994 ; 1444-0903
    ISSN (online) 1445-5994
    ISSN 1444-0903
    DOI 10.1111/imj.16308
    Database MEDical Literature Analysis and Retrieval System OnLINE

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    In stock of ZB MED Cologne/Königswinter

    Zs.A 792: Show issues Location:
    Je nach Verfügbarkeit (siehe Angabe bei Bestand)
    bis Jg. 1994: Bestellungen von Artikeln über das Online-Bestellformular
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    ab Jg. 2022: Lesesaal (EG)
    Zs.MO 424: Show issues

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  4. Article ; Online: Achieving equity: patient demographics and outcomes after surgical and non-surgical procedures in South Australia, 2022.

    Kovoor, Joshua G / Gupta, Aashray K / Bacchi, Stephen / Stretton, Brandon / O'Callaghan, Patrick G / Murphy, Elizabeth / Hugh, Thomas J / Padbury, Robert T / Trochsler, Markus I / Maddern, Guy J

    ANZ journal of surgery

    2024  Volume 94, Issue 1-2, Page(s) 96–102

    Abstract: Background: Although modern Australian healthcare systems provide patient-centred care, the ability to predict and prevent suboptimal post-procedural outcomes based on patient demographics at admission may improve health equity. This study aimed to ... ...

    Abstract Background: Although modern Australian healthcare systems provide patient-centred care, the ability to predict and prevent suboptimal post-procedural outcomes based on patient demographics at admission may improve health equity. This study aimed to identify patient demographic characteristics that might predict disparities in mortality, readmission, and discharge outcomes after either an operative or non-operative procedural hospital admission.
    Methods: This retrospective cohort study included all surgical and non-surgical procedural admissions at three of the four major metropolitan public hospitals in South Australia in 2022. Multivariable logistic regression, with backwards selection, evaluated association between patient demographic characteristics and outcomes up to 90 days post-procedurally.
    Results: 40 882 admissions were included. Increased likelihood of all-cause, post-procedure mortality in-hospital, at 30 days, and 90 days, were significantly associated with increased age (P < 0.001), increased comorbidity burden (P < 0.001), an emergency admission (P < 0.001), and male sex (P = 0.046, P = 0.03, P < 0.001, respectively). Identification as ATSI (P < 0.001) and being born in Australia (P = 0.03, P = 0.001, respectively) were associated with an increased likelihood of 30-day hospital readmission and decreased likelihood of discharge directly home, as was increased comorbidity burden (P < 0.001) and emergency admission (P < 0.001). Being married (P < 0.001) and male sex (P = 0.003) were predictive of an increased likelihood of discharging directly home; in contrast to increased age (P < 0.001) which was predictive of decreased likelihood of this occurring.
    Conclusions: This study characterized several associations between patient demographic factors present on admission and outcomes after surgical and non-surgical procedures, that can be integrated within patient flow pathways through the Australian healthcare system to improve healthcare equity.
    MeSH term(s) Humans ; Male ; South Australia/epidemiology ; Australia ; Retrospective Studies ; Patient Readmission ; Patient Discharge ; Hospitals, Public ; Risk Factors ; Demography
    Language English
    Publishing date 2024-01-30
    Publishing country Australia
    Document type Journal Article
    ZDB-ID 2050749-5
    ISSN 1445-2197 ; 1445-1433 ; 0004-8682
    ISSN (online) 1445-2197
    ISSN 1445-1433 ; 0004-8682
    DOI 10.1111/ans.18871
    Database MEDical Literature Analysis and Retrieval System OnLINE

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    In stock of ZB MED Cologne/Königswinter

    Zs.A 180: Show issues Location:
    Je nach Verfügbarkeit (siehe Angabe bei Bestand)
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    ab Jg. 2022: Lesesaal (EG)

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  5. Article ; Online: Standardizing optimization in surgery.

    Kovoor, Joshua G / Bacchi, Stephen / Gupta, Aashray K / O'Callaghan, Patrick G / Trochsler, Markus I / Maddern, Guy J

    ANZ journal of surgery

    2022  Volume 93, Issue 1-2, Page(s) 24–25

    Language English
    Publishing date 2022-12-22
    Publishing country Australia
    Document type Journal Article
    ZDB-ID 2050749-5
    ISSN 1445-2197 ; 1445-1433 ; 0004-8682
    ISSN (online) 1445-2197
    ISSN 1445-1433 ; 0004-8682
    DOI 10.1111/ans.18201
    Database MEDical Literature Analysis and Retrieval System OnLINE

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    In stock of ZB MED Cologne/Königswinter

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    Je nach Verfügbarkeit (siehe Angabe bei Bestand)
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  6. Article ; Online: Get out what you put in: optimising electronic medical record data.

    Stretton, Brandon / Kovoor, Joshua / Gupta, Aashray / Hains, Lewis / Bacchi, Stephen / Wong, Bianca / O'Callaghan, Patrick G / Barreto, Savio / Hugh, Thomas J / Murphy, Elizabeth / Trochsler, Markus / Padbury, Robert / Boyd, Mark / Maddern, Guy

    ANZ journal of surgery

    2023  Volume 93, Issue 9, Page(s) 2056–2058

    MeSH term(s) Humans ; Electronic Health Records
    Language English
    Publishing date 2023-06-11
    Publishing country Australia
    Document type Journal Article
    ZDB-ID 2050749-5
    ISSN 1445-2197 ; 1445-1433 ; 0004-8682
    ISSN (online) 1445-2197
    ISSN 1445-1433 ; 0004-8682
    DOI 10.1111/ans.18559
    Database MEDical Literature Analysis and Retrieval System OnLINE

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    Kategorien

    In stock of ZB MED Cologne/Königswinter

    Zs.A 180: Show issues Location:
    Je nach Verfügbarkeit (siehe Angabe bei Bestand)
    bis Jg. 1994: Bestellungen von Artikeln über das Online-Bestellformular
    Jg. 1995 - 2021: Lesesall (1.OG)
    ab Jg. 2022: Lesesaal (EG)

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  7. Article ; Online: The Adelaide Score: An artificial intelligence measure of readiness for discharge after general surgery.

    Kovoor, Joshua G / Bacchi, Stephen / Gupta, Aashray K / Stretton, Brandon / Malycha, James / Reddi, Benjamin A / Liew, Danny / O'Callaghan, Patrick G / Beltrame, John F / Zannettino, Andrew C / Jones, Karen L / Horowitz, Michael / Dobbins, Christopher / Hewett, Peter J / Trochsler, Markus I / Maddern, Guy J

    ANZ journal of surgery

    2023  Volume 93, Issue 9, Page(s) 2119–2124

    Abstract: Background: This study aimed to examine the performance of machine learning algorithms for the prediction of discharge within 12 and 24 h to produce a measure of readiness for discharge after general surgery.: Methods: Consecutive general surgery ... ...

    Abstract Background: This study aimed to examine the performance of machine learning algorithms for the prediction of discharge within 12 and 24 h to produce a measure of readiness for discharge after general surgery.
    Methods: Consecutive general surgery patients at two tertiary hospitals, over a 2-year period, were included. Observation and laboratory parameter data were stratified into training, testing and validation datasets. Random forest, XGBoost and logistic regression models were evaluated. Each ward round note time was taken as a different event. Primary outcome was classification accuracy of the algorithmic model able to predict discharge within the next 12 h on the validation data set.
    Results: 42 572 ward round note timings were included from 8826 general surgery patients. Discharge occurred within 12 h for 8800 times (20.7%), and within 24 h for 9885 (23.2%). For predicting discharge within 12 h, model classification accuracies for derivation and validation data sets were: 0.84 and 0.85 random forest, 0.84 and 0.83 XGBoost, 0.80 and 0.81 logistic regression. For predicting discharge within 24 h, model classification accuracies for derivation and validation data sets were: 0.83 and 0.84 random forest, 0.82 and 0.81 XGBoost, 0.78 and 0.79 logistic regression. Algorithms generated a continuous number between 0 and 1 (or 0 and 100), representing readiness for discharge after general surgery.
    Conclusions: A derived artificial intelligence measure (the Adelaide Score) successfully predicts discharge within the next 12 and 24 h in general surgery patients. This may be useful for both treating teams and allied health staff within surgical systems.
    MeSH term(s) Humans ; Artificial Intelligence ; Patient Discharge ; Algorithms ; Machine Learning ; Logistic Models
    Language English
    Publishing date 2023-06-01
    Publishing country Australia
    Document type Journal Article
    ZDB-ID 2050749-5
    ISSN 1445-2197 ; 1445-1433 ; 0004-8682
    ISSN (online) 1445-2197
    ISSN 1445-1433 ; 0004-8682
    DOI 10.1111/ans.18546
    Database MEDical Literature Analysis and Retrieval System OnLINE

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    In stock of ZB MED Cologne/Königswinter

    Zs.A 180: Show issues Location:
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