Dataset Information

Factors associated with undertriage in patients classified by the need to visit a hospital by telephone triage: a retrospective cohort study.

ABSTRACT:

Background

Prehospital telephone triage stratifies patients into five categories, "need immediate hospital visit by ambulance," "need to visit a hospital within 1 hour," "need to visit a hospital within 6 hours," "need to visit a hospital within 24 hours," and "do not need a hospital visit" in Japan. However, studies on whether present and past histories cause undertriage are limited in patients triaged as need an early hospital visit. We investigated factors associated with undertriage by comparing patient assessed to be appropriately triaged with those assessed undertriaged.

Methods

We included all patients classified by telephone triage as need to visit a hospital within 1 h and 6 h who used a single after-hours house call (AHHC) medical service in Tokyo, Japan, between November 1, 2019, and November 31, 2020. After home consultation, AHHC doctors classified patients as grade 1 (treatable with over-the-counter medications), 2 (requires hospital or clinic visit), or 3 (requires ambulance transportation). Patients classified as grade 2 and 3 were defined as appropriately triaged and undertriaged, respectively.

Results

We identified 10,742 eligible patients triaged as need to visit a hospital within 1 h and 6 h, including 10,479 (97.6%) appropriately triaged and 263 (2.4%) undertriaged patients. Multivariable logistic regression analyses revealed patients aged 16-64, 65-74, and ≥ 75 years (adjusted odds ratio [OR], 2.40 [95% confidence interval {CI} 1.71-3.36], 8.57 [95% CI 4.83-15.2], and 14.9 [95% CI 9.65-23.0], respectively; reference patients aged < 15 years); those with diabetes mellitus (2.31 [95% CI 1.25-4.26]); those with dementia (2.32 [95% CI 1.05-5.10]); and those with a history of cerebral infarction (1.98 [95% CI 1.01-3.87]) as more likely to be undertriaged.

Conclusions

We found that older adults and patients with diabetes mellitus, dementia, or a history of cerebral infarction were at risk of undertriage in patients triaged as need to visit a hospital within 1 h and 6 h, but further studies are needed to validate these findings.

SUBMITTER: Inokuchi R

PROVIDER: S-EPMC8672574 | biostudies-literature | 2021 Dec

REPOSITORIES: biostudies-literature

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Publications

Factors associated with undertriage in patients classified by the need to visit a hospital by telephone triage: a retrospective cohort study.

Inokuchi Ryota R Jin Xueying X Iwagami Masao M Abe Toshikazu T Ishikawa Masatoshi M Tamiya Nanako N

BMC emergency medicine 20211215 1

<h4>Background</h4>Prehospital telephone triage stratifies patients into five categories, "need immediate hospital visit by ambulance," "need to visit a hospital within 1 hour," "need to visit a hospital within 6 hours," "need to visit a hospital within 24 hours," and "do not need a hospital visit" in Japan. However, studies on whether present and past histories cause undertriage are limited in patients triaged as need an early hospital visit. We investigated factors associated with undertriage ...[more]

PMID: 34911465

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Project description:BackgroundUndertriaged patients have worse outcomes than appropriately triaged patients. Machine learning provides better triage prediction than conventional triage in emergency departments, but no machine learning-based undertriage prediction models have yet been developed for prehospital telephone triage. We developed and validated machine learning models for telephone triage.Materials and methodsWe conducted a retrospective cohort study with the largest after-hour house-call (AHHC) service dataset in Japan. Participants were ≥16 years and used the AHHC service between 1 November 2018 and 31 January 2021. We developed five prediction models based on support vector machine (SVM), lasso regression (LR), random forest (RF), gradient-boosted decision tree (XGB), and deep neural network (DNN). The primary outcome was undertriage, and predictors were telephone triage level and routinely available telephone-based data, including age, sex, 80 chief complaint categories and 10 comorbidities. We measured the area under the receiver operating characteristic curve (AUROC) for all the models.ResultsWe identified 15,442 eligible patients (age: 38.4 ± 16.6, male: 57.2%), including 298 (1.9%; age: 58.2 ± 23.9, male: 55.0%) undertriaged patients. RF and XGB outperformed the other models, with the AUROC values (95% confidence interval; 95% CI) of the SVM, LR, RF, XGB and DNN for undertriage being 0.62 (0.55-0.69), 0.79 (0.74-0.83), 0.81 (0.76-0.86), 0.80 (0.75-0.84) and 0.77 (0.73-0.82), respectively.ConclusionsWe found that RF and XGB outperformed other models. Our findings suggest that machine learning models can facilitate the early detection of undertriage and early intervention to yield substantially improved patient outcomes.KEY MESSAGESUndertriaged patients experience worse outcomes than appropriately triaged patients; thus, we developed machine learning models for predicting undertriage in the prehospital setting. In addition, we identified the predictors of risk factors associated with undertriage.Random forest and gradient-boosted decision tree models demonstrated better prediction performance, and the models identified the risk factors associated with undertriage.Machine learning models aid in the early detection of undertriage, leading to significantly improved patient outcomes and identifying undertriage-associated risk factors, including chief complaint categories, could help prioritize conventional telephone triage protocol revision.

Project description:ObjectivesWe aim to explore undertriage and overtriage in a high-risk patient population and explore patient characteristics and call characteristics associated with undertriage and overtriage in both randomly selected and in high-risk telephone calls to out-of-hours primary care (OOH-PC).DesignNatural quasi-experimental cross-sectional study.SettingTwo Danish OOH-PC services using different telephone triage models: a general practitioner cooperative with GP-led triage and the medical helpline 1813 with computerised decision support system-guided nurse-led triage.ParticipantsWe included audio-recorded telephone triage calls from 2016: 806 random calls and 405 high-risk calls (defined as patients ≥30 years calling with abdominal pain).Main outcome measuresTwenty-four experienced physicians used a validated assessment tool to assess the accuracy of triage. We calculated the relative risk (RR) for clinically relevant undertriage and overtriage for a range of patient characteristics and call characteristics.ResultsWe included 806 randomly selected calls (44 clinically relevant undertriaged and 54 clinically relevant overtriaged) and 405 high-risk calls (32 undertriaged and 24 overtriaged). In high-risk calls, nurse-led triage was associated with significantly less undertriage (RR: 0.47, 95% CI 0.23 to 0.97) and more overtriage (RR: 3.93, 95% CI 1.50 to 10.33) compared with GP-led triage. In high-risk calls, the risk of undertriage was significantly higher for calls during nighttime (RR: 2.1, 95% CI 1.05 to 4.07). Undertriage tended to be more likely for calls concerning patients ≥60 years compared with 30-59 years (11.3% vs 6.3%) in high-risk calls. However, this result was not significant.ConclusionNurse-led triage was associated with less undertriage and more overtriage compared with GP-led triage in high-risk calls. This study may suggest that to minimise undertriage, the triage professionals should pay extra attention when a call occurs during nighttime or concerns elderly. However, this needs confirmation in future studies.

Project description:OBJECTIVE:To investigate the appropriateness of cases presenting to the emergency department (ED) following ambulance-based secondary telephone triage. DESIGN:A pragmatic retrospective cohort analysis of all the planned and unplanned ED presentations within 48 hours of a secondary telephone triage. SETTING:The secondary telephone triage service, called the Referral Service, and the hospitals were located in metropolitan Melbourne, Australia and operated 24 hours a day, servicing 4.25 million people. The Referral Service provides an in-depth secondary triage of cases classified as low acuity when calling the Australian emergency telephone number. POPULATION:Cases triaged by the Referral Service between September 2009 and June 2012 were linked to ED and hospital admission records (N=44,523). Planned ED presentations were cases referred to the ED following the secondary triage, unplanned ED presentations were cases that presented despite being referred to alternative care pathways. MAIN OUTCOME MEASURES:Appropriateness was measured using an ED suitability definition and hospital admission rates. These were compared with mean population data which consisted of all of the ED presentations for the state (termed the 'average Victorian ED presentation'). RESULTS:Planned ED presentations were more likely to be ED suitable than unplanned ED presentations (OR 1.62; 95% CI 1.5 to 1.7; p<0.001) and the average Victorian ED presentation (OR 1.85; 95% CI 1.01 to 3.4; p=0.046). They were also more likely to be admitted to the hospital than the unplanned ED presentation (OR 1.5; 95% CI 1.4 to 1.6; p<0.001) and the average Victorian ED presentation (OR 2.3, 95% CI 2.24 to 2.33; p<0.001). Just under 15% of cases diverted away from the emergency care pathways presented in the ED (unplanned ED attendances), and 9.5% of all the alternative care pathway cases were classified as ED suitable and 6.5% were admitted to hospital. CONCLUSIONS:Secondary telephone triage was able to appropriately identify many ED suitable cases, and while most cases referred to alternative care pathways did not present in the ED. Further research is required to establish that these were not inappropriately triaged away from the emergency care pathways.

Project description:BackgroundIn the recent decades, the use of computerized decision support software (CDSS)-integrated telephone triage (TT) has become an important tool for managing rising healthcare demands and overcrowding in the emergency department. Though these services have generally been shown to be effective, large gaps in the literature exist with regards to the overall quality of these systems. In the current systematic review, we aim to document the consistency of decisions that are generated in CDSS-integrated TT. Furthermore, we also seek to map those factors in the literature that have been identified to have an impact on the consistency of generated triage decisions.MethodsAs part of the TRANS-SENIOR international training and research network, a systematic review of the literature was conducted in November 2019. PubMed, Web of Science, CENTRAL, and the CINAHL database were searched. Quantitative articles including a CDSS component and addressing consistency of triage decisions and/or factors associated with triage decisions were eligible for inclusion in the current review. Studies exploring the use of other types of digital support systems for triage (i.e. web chat, video conferencing) were excluded. Quality appraisal of included studies were performed independently by two authors using the Methodological Index for Non-Randomized Studies.ResultsFrom a total of 1551 records that were identified, 39 full-texts were assessed for eligibility and seven studies were included in the review. All of the studies (n = 7) identified as part of our search were observational and were based on nurse-led telephone triage. Scientific efforts investigating our first aim was very limited. In total, two articles were found to investigate the consistency of decisions that are generated in CDSS-integrated TT. Research efforts were targeted largely towards the second aim of our study-all of the included articles reported factors related to the operator- (n = 6), patient- (n = 1), and/or CDSS-integrated (n = 2) characteristics to have an influence on the consistency of CDSS-integrated TT decisions.ConclusionTo date, some efforts have been made to better understand how the use of CDSS-integrated TT systems may vary across settings. In general, however, the evidence-base surrounding this field of literature is largely inconclusive. Further evaluations must be prompted to better understand this area of research.Protocol registrationThe protocol for this study is registered in the PROSPERO database (registration number: CRD42020146323).

Project description:BackgroundTelephone triage is used to optimise patient flow in emergency primary healthcare. Poor communication can lead to misunderstandings and compromise patient safety. To improve quality, a comprehensive understanding of factors affecting communication in medical call centres in primary care is needed. The aim of this review was to identify such factors and to describe how they affect communication during telephone triage.MethodA mixed-method systematic review was performed. In April 2021 and June 2023, MEDLINE, Embase, CINAHL, and Web of Science were searched for original studies describing communication during telephone triage in primary care medical call centres handling all types of medical problems from an unselected population. All studies were screened by two authors, blinded to each other's decisions. Disagreements were resolved by a third author. A framework was created by the thematic synthesis of the qualitative data and later used to synthesise the quantitative data. By using convergent integrated synthesis, the qualitative and quantitative findings were integrated. The Mixed Methods Appraisal Tool was used to assess methodological limitations.ResultsOut of 5087 studies identified in the search, 62 studies were included, comprising 40 qualitative, 16 quantitative and six mixed-method studies. Thirteen factors were identified and organised into four main themes: organisational factors, factors related to the operator, factors related to the caller and factors in the interaction. Organisational factors included availability, working conditions and decision support systems. Factors related to the operator were knowledge and experience, personal qualities and communication strategies. Factors related to the caller were individual differences and the presented medical problem. Factors in the interaction were faceless communication, connection between operator and caller, third-person caller and communication barriers. The factors seem interrelated, with organisational factors affecting all parts of the conversation, and the operator's communication in particular.ConclusionMany factors affect the structure, content, and flow of the conversation. The operators influence the communication directly but rely on the organisation to create a working environment that facilitates good communication. The results are mainly supported by qualitative studies and further studies are needed to explore and substantiate the relevance and effect of individual factors.Systematic review registrationPROSPERO CRD42022298022.

Project description:ImportanceUndertriaging patients who are at increased risk for postoperative complications after surgical procedures to low-acuity hospital wards (ie, floors) rather than highly vigilant intensive care units (ICUs) may be associated with risk of unrecognized decompensation and worse patient outcomes, but evidence for these associations is lacking.ObjectiveTo test the hypothesis that postoperative undertriage is associated with increased mortality and morbidity compared with risk-matched ICU admission.Design, setting, and participantsThis longitudinal cross-sectional study was conducted using data from the University of Florida Integrated Data Repository on admissions to a university hospital. Included patients were individuals aged 18 years or older who were admitted after a surgical procedure from June 1, 2014, to August 20, 2020. Data were analyzed from April through August 2021.ExposuresWard admissions were considered undertriaged if their estimated risk for hospital mortality or prolonged ICU stay (ie, ≥48 hours) was in the top quartile among all inpatient surgical procedures according to a validated machine-learning model using preoperative and intraoperative electronic health record features available at surgical procedure end time. A nearest neighbors algorithm was used to identify a risk-matched control group of ICU admissions.Main outcomes and measuresThe primary outcomes of hospital mortality and morbidity were compared among appropriately triaged ward admissions, undertriaged wards admissions, and a risk-matched control group of ICU admissions.ResultsAmong 12 348 postoperative ward admissions, 11 042 admissions (89.4%) were appropriately triaged (5927 [53.7%] women; median [IQR] age, 59 [44-70] years) and 1306 admissions (10.6%) were undertriaged and matched with a control group of 2452 ICU admissions. The undertriaged group, compared with the control group, had increased median [IQR] age (64 [54-74] years vs 62 [50-73] years; P = .001) and increased proportions of women (649 [49.7%] women vs 1080 [44.0%] women; P < .001) and admitted patients with do not resuscitate orders before first surgical procedure (53 admissions [4.1%] vs 27 admissions [1.1%]); P < .001); 207 admissions that were undertriaged (15.8%) had subsequent ICU admission. In the validation cohort, hospital mortality and prolonged ICU stay estimations had areas under the receiver operating characteristic curve of 0.92 (95% CI, 0.91-0.93) and 0.92 (95% CI, 0.92-0.92), respectively. The undertriaged group, compared with the control group, had similar incidence of prolonged mechanical ventilation (32 admissions [2.5%] vs 53 admissions [2.2%]; P = .60), decreased median (IQR) total costs for admission ($26 900 [$18 400-$42 300] vs $32 700 [$22 700-$48 500]; P < .001), increased median (IQR) hospital length of stay (8.1 [5.1-13.6] days vs 6.0 [3.3-9.3] days, P < .001), and increased incidence of hospital mortality (19 admissions [1.5%] vs 17 admissions [0.7%]; P = .04), discharge to hospice (23 admissions [1.8%] vs 14 admissions [0.6%]; P < .001), unplanned intubation (45 admissions [3.4%] vs 49 admissions [2.0%]; P = .01), and acute kidney injury (341 admissions [26.1%] vs 477 admissions [19.5%]; P < .001).Conclusions and relevanceThis study found that admitted patients at increased risk for postoperative complications who were undertriaged to hospital wards had increased mortality and morbidity compared with a risk-matched control group of admissions to ICUs. Postoperative undertriage was identifiable using automated preoperative and intraoperative data as features in real-time machine-learning models.

Dataset Information

Factors associated with undertriage in patients classified by the need to visit a hospital by telephone triage: a retrospective cohort study.

Background

Methods

Results

Conclusions

Publications

Factors associated with undertriage in patients classified by the need to visit a hospital by telephone triage: a retrospective cohort study.

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