Preoperative anaesthesia triage with a patient‐centred system—A prospective clinical study

Molin, Clara; Rovsing, Marie Louise; Meyhoff, Christian S.

doi:10.1111/aas.13678

Cited by 4 publications

(3 citation statements)

References 16 publications

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“…[24][25][26]34,38 Investigators have previously described developing and implementing scoring systems for POM triage that are based on the risk of the patient being ASA score III or IV. 24,26,[39][40][41][42][43] However, given the inherent subjectivity and poor inter-rater reliability in the assignment of ASA score by providers, 40,44,45 we questioned whether training a model to predict ASA will yield the most consistent approach to POM triage. Our analysis demonstrates that compared with ASA, CAST exhibited greater discrimination for poor surgical outcomes.…”

Section: Discussionmentioning

confidence: 99%

“…Multiple different POM triage practices are described in the literature, including clinical judgement alone, 18,25 patient questionnaires, 23,36,37 or scoring systems based on patient and surgical procedure characteristics. [24][25][26]34,38 Investigators have previously described developing and implementing scoring systems for POM triage that are based on the risk of the patient being ASA score III or IV. 24,26,[39][40][41][42][43] However, given the inherent subjectivity and poor inter-rater reliability in the assignment of ASA score by providers, 40,44,45 we questioned whether training a model to predict ASA will yield the most consistent approach to POM triage.…”

Section: Discussionmentioning

confidence: 99%

“…17,18 However, there is substantial variation in the request for outpatient POM consultation, 19 even among patients with high comorbidities undergoing major elective surgeries, 20,21 leading to the potential for both under- or over-utilization of POM resources. Multiple triage approaches have been described, including those based on patient questionnaires, 22 surgeon referrals, 18 screening by nurses or anesthesiologists, 23,24 and procedure characteristics. 25,26 However, few studies have compared the performance of POM triage algorithms in distinguishing low and high risk surgical patients.…”

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confidence: 99%

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Development and Validation of an Electronic Health Record-based Score for Triage to Perioperative Medicine

Corbin

Myers

et al. 2021

Annals of Surgery

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Objective: To develop an electronic health record-based risk model for perioperative medicine (POM) triage and compare this model with legacy triage practices that were based on clinician assessment. Summary of Background Data: POM clinicians seek to address the increasingly complex medical needs of patients prior to scheduled surgery. Identifying which patients might derive the most benefit from evaluation is challenging. Methods: Elective surgical cases performed within a health system 2014– 2019 (N = 470,727) were used to develop a predictive score, called the Comorbidity Assessment for Surgical Triage (CAST) score, using split validation. CAST incorporates patient and surgical case characteristics to predict the risk of 30-day post-operative morbidity, defined as a composite of mortality and major NSQIP complications. Thresholds of CAST were then selected to define risk groups, which correspond with triage to POM appointments of different durations and modalities. The predictive discrimination CAST score was compared with the surgeon’s assessments of patient complexity and the American Society of Anesthesiologists class. Results: The CAST score demonstrated a significantly higher discrimination for predicting post-operative morbidity (area under the receiver operating characteristic curve 0.75) than the surgeon’s complexity designation (0.63; P < 0.001) or the American Society of Anesthesiologists (0.65; P < 0.001) (Fig. 1). Incorporating the complexity designation in the CAST model did not significantly alter the discrimination (0.75; P = 0.098). Compared with the complexity designation, classification based on CAST score groups resulted a net reclassification improvement index of 10.4% (P < 0.001) (Table 1). Conclusion: A parsimonious electronic health record-based predictive model demonstrates improved performance for identifying pre-surgical patients who are at risk than previously-used assessments for POM triage.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

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confidence: 99%

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Development and Validation of an Electronic Health Record-based Score for Triage to Perioperative Medicine

Corbin

Myers

et al. 2021

Annals of Surgery

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Differences between patients in whom physicians agree versus disagree about the preoperative diagnosis of heart failure

Kamyszek

Newman

Ragheb

et al. 2023

Journal of Clinical Anesthesia

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Pre-operative triAge proCedure to streaMline elective surgicAl patieNts (PACMAN) improves efficiency by selecting patients eligible for phone consultation

Di Biase,

van der Zwaard,

Aarts

et al. 2024

European Journal of Anaesthesiology

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BACKGROUND Pre-operative screening is a high volume task consuming time and resource. Streamlining patient flow by gathering information in advance reduces costs, optimises resources and diminishes patient burden whilst maintaining safety of care. OBJECTIVE To evaluate whether ‘Pre-operative triAge proCedure to streaMline elective surgicAl patieNts’ (PACMAN) is able to improve pre-operative screening by selecting patients eligible for evaluation by telephone. DESIGN A single-centre, retrospective, observational cohort analysis. SETTING A tertiary medical teaching hospital in ‘s-Hertogenbosch, The Netherlands. PATIENTS AND METHODS Adults scheduled for clinical interventions under procedural sedation and all types of elective medium or low risk surgery with anaesthetic guidance were eligible. Patients answered a questionnaire to calculate the PACMAN score. This score combined with risk factors related to surgery determines suitability for phone consultation (PhC) or the need for an in-person consultation (in-PC). INTERVENTION Evaluation of standard care. MAIN OUTCOME MEASURES Primary outcome was the reduction in number of in-PCs. Secondary outcomes included reliability of PACMAN, peri-operative patient outcomes and cost-effectiveness. RESULTS Of 965 patients triaged by PACMAN, 705 (73.1%) were identified as suitable for a PhC. Of those, 688 (97.6%) were classified American Society of Anesthesiologists Physical Status (ASA-PS) I to II or III with stable comorbidities. Of the 260 in-PC patients, 47.4% were classified ASA-PS III with unstable comorbidities or ASA-PS IV. The overall incidence of unanticipated adverse peri-operative events was 1.3%. Finally, implementation of PACMAN led to a 20% increase in pre-operative department efficiency due to better deployment of personnel and resources. CONCLUSION Implementation of PACMAN resulted in a 73.1% reduction in pre-operative in-PCs at our hospital. Given the increasing pressure on healthcare systems globally, we suggest developing further optimisation and integration of smart triage solutions into the pre-operative process. TRIAL REGISTRATION ClinicalTrials.gov Identifier: NCT06148701

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Preoperative anaesthesia triage with a patient‐centred system—A prospective clinical study

Cited by 4 publications

References 16 publications

Development and Validation of an Electronic Health Record-based Score for Triage to Perioperative Medicine

Development and Validation of an Electronic Health Record-based Score for Triage to Perioperative Medicine

Differences between patients in whom physicians agree versus disagree about the preoperative diagnosis of heart failure

Pre-operative triAge proCedure to streaMline elective surgicAl patieNts (PACMAN) improves efficiency by selecting patients eligible for phone consultation

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