External validation of triage tools for adults with suspected COVID-19 in a middle-income setting: an observational cohort study.

BACKGROUND: Tools proposed to triage ED acuity in suspected COVID-19 were derived and validated in higher income settings during early waves of the pandemic. We estimated the accuracy of seven risk-stratification tools recommended to predict severe illness in the Western Cape, South Africa. METHODS: An observational cohort study using routinely collected data from EDs across the Western Cape, from 27 August 2020 to 11 March 2022, was conducted to assess the performance of the PRIEST (Pandemic Respiratory Infection Emergency System Triage) tool, NEWS2 (National Early Warning Score, version 2), TEWS (Triage Early Warning Score), the WHO algorithm, CRB-65, Quick COVID-19 Severity Index and PMEWS (Pandemic Medical Early Warning Score) in suspected COVID-19. The primary outcome was intubation or non-invasive ventilation, death or intensive care unit admission at 30 days. RESULTS: Of the 446 084 patients, 15 397 (3.45%, 95% CI 34% to 35.1%) experienced the primary outcome. Clinical decision-making for inpatient admission achieved a sensitivity of 0.77 (95% CI 0.76 to 0.78), specificity of 0.88 (95% CI 0.87 to 0.88) and the negative predictive value (NPV) of 0.99 (95% CI 0.99 to 0.99). NEWS2, PMEWS and PRIEST scores achieved good estimated discrimination (C-statistic 0.79 to 0.82) and identified patients at risk of adverse outcomes at recommended cut-offs with moderate sensitivity (>0.8) and specificity ranging from 0.41 to 0.64. Use of the tools at recommended thresholds would have more than doubled admissions, with only a 0.01% reduction in false negative triage. CONCLUSION: No risk score outperformed existing clinical decision-making in determining the need for inpatient admission based on prediction of the primary outcome in this setting. Use of the PRIEST score at a threshold of one point higher than the previously recommended best approximated existing clinical accuracy.

Prognostic accuracy of triage tools for adults with suspected COVID-19 in a prehospital setting: an observational cohort study.

BACKGROUND: Tools proposed to triage patient acuity in COVID-19 infection have only been validated in hospital populations. We estimated the accuracy of five risk-stratification tools recommended to predict severe illness and compared accuracy to existing clinical decision making in a prehospital setting. METHODS: An observational cohort study using linked ambulance service data for patients attended by Emergency Medical Service (EMS) crews in the Yorkshire and Humber region of England between 26 March 2020 and 25 June 2020 was conducted to assess performance of the Pandemic Respiratory Infection Emergency System Triage (PRIEST) tool, National Early Warning Score (NEWS2), WHO algorithm, CRB-65 and Pandemic Medical Early Warning Score (PMEWS) in patients with suspected COVID-19 infection. The primary outcome was death or need for organ support. RESULTS: Of the 7549 patients in our cohort, 17.6% (95% CI 16.8% to 18.5%) experienced the primary outcome. The NEWS2 (National Early Warning Score, version 2), PMEWS, PRIEST tool and WHO algorithm identified patients at risk of adverse outcomes with a high sensitivity (>0.95) and specificity ranging from 0.3 (NEWS2) to 0.41 (PRIEST tool). The high sensitivity of NEWS2 and PMEWS was achieved by using lower thresholds than previously recommended. On index assessment, 65% of patients were transported to hospital and EMS decision to transfer patients achieved a sensitivity of 0.84 (95% CI 0.83 to 0.85) and specificity of 0.39 (95% CI 0.39 to 0.40). CONCLUSION: Use of NEWS2, PMEWS, PRIEST tool and WHO algorithm could improve sensitivity of EMS triage of patients with suspected COVID-19 infection. Use of the PRIEST tool would improve sensitivity of triage without increasing the number of patients conveyed to hospital.

Novel insights into views towards H1N1 during the 2009 Pandemic: a thematic analysis of Twitter data.

BACKGROUND: Infectious disease outbreaks have the potential to cause a high number of fatalities and are a very serious public health risk. OBJECTIVES: Our aim was to utilise an indepth method to study a period of time where the H1N1 Pandemic of 2009 was at its peak. METHODS: A data set of n = 214 784 tweets was retrieved and filtered, and the method of thematic analysis was used to analyse the data. RESULTS: Eight key themes emerged from the analysis of data: emotion and feeling, health related information, general commentary and resources, media and health organisations, politics, country of origin, food, and humour and/or sarcasm. DISCUSSION: A major novel finding was that due to the name 'swine flu', Twitter users had the belief that pigs and pork could host and/or transmit the virus. Our paper also considered the methodological implications for the wider field of library and information science as well as specific implications for health information and library workers. CONCLUSIONS: Novel insights were derived on how users communicate about disease outbreaks on social media platforms. Our study also provides an innovative methodological contribution because it was found that by utilising an indepth method it was possible to extract greater insight into user communication.

Sharing and Empathy in Digital Spaces: Qualitative Study of Online Health Forums for Breast Cancer and Motor Neuron Disease (Amyotrophic Lateral Sclerosis).

BACKGROUND: The availability of an increasing number of online health forums has altered the experience of living with a health condition, as more people are now able to connect and support one another. Empathy is an important component of peer-to-peer support, although little is known about how empathy develops and operates within online health forums. OBJECTIVE: The aim of this paper is to explore how empathy develops and operates within two online health forums for differing health conditions: breast cancer and motor neuron disease (MND), also known as amyotrophic lateral sclerosis. METHODS: This qualitative study analyzed data from two sources: interviews with forum users and downloaded forum posts. Data were collected from two online health forums provided by UK charities: Breast Cancer Care and the Motor Neurone Disease Association. We analyzed 84 threads from the breast cancer forum and 52 from the MND forum. Threads were purposively sampled to reflect varied experiences (eg, illness stages, topics of conversation, and user characteristics). Semistructured interviews were conducted with 14 Breast Cancer Care forum users and five users of the MND forum. All datasets were analyzed thematically using Braun and Clarke's six-phase approach and combined to triangulate the analysis. RESULTS: We found that empathy develops and operates through shared experiences and connections. The development of empathy begins outside the forum with experiences of illness onset and diagnosis, creating emotional and informational needs. Users came to the forum and found their experiences and needs were shared and understood by others, setting the empathetic tone and supportive ethos of the forum. The forum was viewed as both a useful and meaningful space in which they could share experiences, information, and emotions, and receive empathetic support within a supportive and warm atmosphere. Empathy operated through connections formed within this humane space based on similarity, relationships, and shared feelings. Users felt a need to connect to users who they felt were like themselves (eg, people sharing the same specific diagnosis). They formed relationships with other users. They connected based on the emotional understanding of ill health. Within these connections, empathic communication flourished. CONCLUSIONS: Empathy develops and operates within shared experiences and connections, enabled by structural possibilities provided by the forums giving users the opportunity and means to interact within public, restricted, and more private spaces, as well as within groups and in one-to-one exchanges. The atmosphere and feeling of both sites and perceived audiences were important facilitators of empathy, with users sharing a perception of virtual communities of caring and supportive people. Our findings are of value to organizations hosting health forums and to health professionals signposting patients to additional sources of support.

Factors influencing the quality of vital sign data in electronic health records: A qualitative study.

AIMS AND OBJECTIVES: To investigate reasons for inadequate documentation of vital signs in an electronic health record. BACKGROUND: Monitoring vital signs is crucial to detecting and responding to patient deterioration. The ways in which vital signs are documented in electronic health records have received limited attention in the research literature. A previous study revealed that vital signs in an electronic health record were incomplete and inconsistent. DESIGN: Qualitative study. METHODS: Qualitative study. Data were collected by observing (68 hr) and interviewing nurses (n = 11) and doctors (n = 3), and analysed by thematic analysis to examine processes for measuring, documenting and retrieving vital signs in four clinical settings in a 353-bed hospital. RESULTS: We identified two central reasons for inadequate vital sign documentation. First, there was an absence of firm guidelines for observing patients' vital signs, resulting in inconsistencies in the ways vital signs were recorded. Second, there was a lack of adequate facilities in the electronic health record for recording vital signs. This led to poor presentation of vital signs in the electronic health record and to staff creating paper "workarounds." CONCLUSIONS: This study demonstrated inadequate routines and poor facilities for vital sign documentation in an electronic health record, and makes an important contribution to knowledge by identifying problems and barriers that may occur. Further, it has demonstrated the need for improved facilities for electronic documentation of vital signs. RELEVANCE TO CLINICAL PRACTICE: Patient safety may have been compromised because of poor presentation of vital signs. Thus, our results emphasised the need for standardised routines for monitoring patients. In addition, designers should consult the clinical end-users to optimise facilities for electronic documentation of vital signs. This could have a positive impact on clinical practice and thus improve patient safety.

Development of Trust in an Online Breast Cancer Forum: A Qualitative Study.

BACKGROUND: Online health forums provide peer support for a range of medical conditions including life-threatening and terminal illnesses. Trust is an important component of peer-to-peer support, although relatively little is known about how trust forms within online health forums. OBJECTIVE: The aim of this paper is to examine how trust develops and influences sharing among users of an online breast cancer forum. METHODS: An interpretive qualitative approach was adopted. Data were collected from forum posts from 135 threads on 9 boards on the UK charity, Breast Cancer Care (BCC). Semistructured interviews were conducted with 14 BCC forum users. Both datasets were analyzed thematically using Braun and Clarke's approach and combined to triangulate analysis. RESULTS: Trust operates in 3 dimensions, structural, relational, and temporal, and these intersect with each other and do not operate in isolation. The structural dimension relates to how the affordances and formal rules of the site affected trust. The relational dimension refers to how trust was necessarily experienced in interactions with other forum users: it emerged within relationships and was a social phenomenon. The temporal dimension relates to how trust changed over time and was influenced by the length of time users spent on the forum. CONCLUSIONS: Trust is a process that changes over time and which is influenced by structural features of the forum, as well as informal but collectively understood relational interactions among forum users. The study provides a better understanding of how the intersecting structural, relational, and temporal aspects that support the development of trust facilitate sharing in online environments. These findings will help organizations developing online health forums.

Individual factors affecting preferences for feedback message tactics in the contexts of physical activity.

Tailored feedback on personal physical activity behavior has been used to inform individuals and promote physical activity among different populations. This study aimed to increase the understanding of factors associated with young men's preferences for feedback message tactics in the context of physical activity and exercise. How preferences vary was analyzed in terms of the self-reported physical activity, stage of exercise behavior change, exercise self-efficacy, objectively measured physical health status, and sociodemographic characteristics of young Finnish men. Population-based survey data, including physiological measurements (n = 525), were collected at the Finnish Defence Forces' call-ups in the city of Oulu, Finland, in September 2011. The results indicate that the stage of exercise behavior change, exercise self-efficacy, physical health status, and educational level are associated with a preference for normative and ipsative comparison. Multivariate logistic regression models show that an advanced stage of exercise behavior change and education in the academic track of an upper secondary school are independent predictors of preferring ipsative and normative physical activity feedback among young men. The study provides new insights into how the stage of behavior change influences health information behavior and is in line with studies emphasizing social factors--including education--as being important in shaping health-related behavior. These factors could form the basis for tailoring information when designing health promotion.

Prognostic accuracy of eight triage scores in suspected COVID-19 in an Emergency Department low-income setting: An observational cohort study.

Introduction: Previous studies deriving and validating triage scores for patients with suspected COVID-19 in Emergency Department settings have been conducted in high- or middle-income settings. We assessed eight triage scores' accuracy for death or organ support in patients with suspected COVID-19 in Sudan. Methods: We conducted an observational cohort study using Covid-19 registry data from eight emergency unit isolation centres in Khartoum State, Sudan. We assessed performance of eight triage scores including: PRIEST, LMIC-PRIEST, NEWS2, TEWS, the WHO algorithm, CRB-65, Quick COVID-19 Severity Index and PMEWS in suspected COVID-19. A composite primary outcome included death, ventilation or ICU admission. Results: In total 874 (33.84 %, 95 % CI:32.04 % to 35.69 %) of 2,583 patients died, required intubation/non-invasive ventilation or HDU/ICU admission . All risk-stratification scores assessed had worse estimated discrimination in this setting, compared to studies conducted in higher-income settings: C-statistic range for primary outcome: 0.56-0.64. At previously recommended thresholds NEWS2, PRIEST and LMIC-PRIEST had high estimated sensitivities (≥0.95) for the primary outcome. However, the high baseline risk meant that low-risk patients identified at these thresholds still had a between 8 % and 17 % risk of death, ventilation or ICU admission. Conclusion: None of the triage scores assessed demonstrated sufficient accuracy to be used clinically. This is likely due to differences in the health care system and population (23 % of patients died) compared to higher-income settings in which the scores were developed. Risk-stratification scores developed in this setting are needed to provide the necessary accuracy to aid triage of patients with suspected COVID-19.

The association of geographical location and neighbourhood deprivation with older people's use of NHS Direct: a population-based study.

BACKGROUND: no research has investigated how older people's use of NHS Direct, the 24-h telephone health advice and information service in England and Wales, varies according to geographical location and deprivation. OBJECTIVES: to describe the geographic pattern of older people's use of NHS Direct and examine the relationship between service use and deprivation. DESIGN: descriptive, exploratory, cross-sectional, population-based study. SETTING: calls to all 32-NHS Direct contact centres in England/Wales. PARTICIPANTS: people aged 65 years and above who used NHS Direct between 1 December 2007 and 30 November 2008. RESULTS: differences in older people's use of NHS Direct were observed in England and Wales. In England, the call rate was highest in Yorkshire and the Humber and was lowest in the West Midlands. At the postcode level, the rate of calls ranged from 0.167 (Blackburn) to 0.011 (Carlisle) per person per annum. In England, but not in Wales, the level of deprivation was associated with the rate of calls, older people living in the most deprived areas had the highest rate of calls to NHS Direct. CONCLUSIONS: the results are useful for future planning to meet the needs of older people, and in informing national policies for the development of NHS Direct.

What factors influence emergency department staff attitudes towards using information technology?

OBJECTIVES: Information technology (IT) has an important role in the emergency department (ED) functioning, but staff attitudes can influence the way IT is used. Qualitative research into the perceptions of the ED staff has identified a variety of individual, environmental and system factors that may influence attitudes towards using IT. The authors aimed to determine which factors predict attitudes towards using IT and which factors are the most influential. METHODS: Findings from a previous qualitative study were used to develop a self-administered questionnaire measuring individual, environmental and system factors, along with staff attitudes towards using IT. The questionnaire was sent to 535 staff working in three English EDs. Simple linear regression was used to examine the relationship between each potential predictor and user attitude, and multiple regression was used to identify the most important predictors. RESULTS: Completed questionnaires were returned by 362/535 participants (68%). The factors with the strongest positive association with staff attitudes towards using IT were the perceived individual impact of technology (r(2)=39%, p<0.001), perceived usefulness (r(2)=7%, p<0.001), perceived ease of use (r(2)=2%, p=0.006), perceived subjective norms (r(2)=1%, p=0.013) and computer experience (r(2)=1%, p=0.034). CONCLUSION: The perceived individual impact of technology is the most important factor in determining ED staff attitude towards using IT. The ED staff are more likely to view using IT systems positively if they can see direct individual benefits arising from their use.

Information needs of clinicians and non-clinicians in the Emergency Department: a qualitative study.

BACKGROUND: Identifying the information needs of Emergency Department (ED) staff and sources of information that they use can help to improve efficiency and effectiveness in the ED. As Emergency Medicine has unique characteristics, information needs of the Emergency Department (ED) staff might be different from other settings. However, few studies have investigated the information needs of ED staff and the sources of information that they use. OBJECTIVES: We aimed to investigate the information needs of ED staff and the sources of information that they used in their practice. METHODS: It was a qualitative study, in which data were collected using semi-structured interviews and 34 ED staff were interviewed in total. To analyse data, the method of framework analysis was used. RESULTS: Different types of information needs and sources of information were found in the ED. Patient information was considered the most important type of information, and verbal communication was the most frequently used source of information. CONCLUSION: The variety of information used in the ED shows task complexity in this department which might not be simply addressed by technology. Further research is needed to identify how computerised information systems can be improved to meet users' information needs in the ED.

Socioeconomic Background and Self-Reported Sleep Quality in Older Adults during the COVID-19 Pandemic: An Analysis of the English Longitudinal Study of Ageing (ELSA).

The COVID-19 pandemic negatively impacted sleep quality. However, research regarding older adults' sleep quality during the pandemic has been limited. This study examined the association between socioeconomic background (SEB) and older adults' sleep quality during the COVID-19 pandemic. Data on 7040 adults aged ≥50 were acquired from a COVID-19 sub-study of the English Longitudinal Study of Ageing (ELSA). SEB was operationalized using educational attainment, previous financial situation, and concern about the future financial situation. Sociodemographic, mental health, physical health, and health behavior variables were included as covariates. Chi-squared tests and binary logistic regression were used to examine associations between SEB and sleep quality. Lower educational attainment and greater financial hardship and concerns were associated with poor sleep quality. The relationship between educational attainment and sleep quality was explained by the financial variables, while the relationship between previous financial difficulties and sleep quality was explained by physical health and health behavior variables. Greater financial concerns about the future, poor mental health, and poor physical health were independent risk factors for poor sleep quality in older adults during the pandemic. Healthcare professionals and service providers should consider these issues when supporting older patients with sleep problems and in promoting health and wellness.

Social Support in a Diabetes Online Community: Mixed Methods Content Analysis.

BACKGROUND: Patients with diabetes may experience different needs according to their diabetes stage. These needs may be met via online health communities in which individuals seek health-related information and exchange different types of social support. Understanding the social support categories that may be more important for different diabetes stages may help diabetes online communities (DOCs) provide more tailored support to web-based users. OBJECTIVE: This study aimed to explore and quantify the categorical patterns of social support observed in a DOC, taking into consideration users' different diabetes stages, including prediabetes, type 2 diabetes (T2D), T2D with insulin treatment, and T2D remission. METHODS: Data were collected from one of the largest DOCs in Europe: Diabetes.co.uk. Drawing on a mixed methods content analysis, a qualitative content analysis was conducted to explore what social support categories could be identified in users' posts. A total of 1841 posts were coded by 5 human annotators according to a modified version of the Social Support Behavior Code, including 7 different social support categories: achievement, congratulations, network support, seeking emotional support, seeking informational support, providing emotional support, and providing informational support. Subsequently, quantitative content analysis was conducted using chi-square post hoc analysis to compare the most prominent social support categories across different stages of diabetes. RESULTS: Seeking informational support (605/1841, 32.86%) and providing informational support (597/1841, 32.42%) were the most frequent categories exchanged among users. The overall distribution of social support categories was significantly different across the diabetes stages (χ218=287.2; P<.001). Users with prediabetes sought more informational support than those in other stages (P<.001), whereas there were no significant differences in categories posted by users with T2D (P>.001). Users with T2D under insulin treatment provided more informational and emotional support (P<.001), and users with T2D in remission exchanged more achievement (P<.001) and network support (P<.001) than those in other stages. CONCLUSIONS: This is the first study to highlight what, how, and when different types of social support may be beneficial at different stages of diabetes. Multiple stakeholders may benefit from these findings that may provide novel insights into how these categories can be strategically used and leveraged to support diabetes management.

Can all healthy adults use the current evidential breath alcohol analysers? An investigation using a large spirometry database.

People failing to give a specimen of breath at a police station are assumed to be deliberately obstructive and are charged with Failure to Provide under the Road Traffic Act 1988. However, spirometry records of 281,210 healthy individuals from UK BioBank showed that a significant minority cannot use existing evidential breath analysis machines. Women were three times more likely to be unable to use them than men (1.64% vs 0.54%) with the risk rising with age six-fold from those in their 40s (0.43%) to 2.7% in their 70s, with women more affected (0.65% to 3.8%). Short stature was a further risk factor: 2.6% of men and 3.8% of women below the 2nd percentile of height could not use the current machines, with almost one in ten elderly, short women unable to do so, while smokers aged 50+ were twice as likely as non-smokers of the same age to be unable to provide breath specimens.

An unsupervised learning approach to diagnosing Alzheimer's disease using brain magnetic resonance imaging scans.

BACKGROUND: Alzheimer's disease (AD) is the most common cause of dementia, characterised by behavioural and cognitive impairment. Due to the lack of effectiveness of manual diagnosis by doctors, machine learning is now being applied to diagnose AD in many recent studies. Most research developing machine learning algorithms to diagnose AD use supervised learning to classify magnetic resonance imaging (MRI) scans. However, supervised learning requires a considerable volume of labelled data and MRI scans are difficult to label. OBJECTIVE: This study applied a statistical method and unsupervised learning methods to discriminate between scans from cognitively normal (CN) and people with AD using a limited number of labelled structural MRI scans. METHODS: We used two-sample t-tests to detect the AD-relevant regions, and then employed an unsupervised learning neural network to extract features from the regions. Finally, a clustering algorithm was implemented to discriminate between CN and AD data based on the extracted features. The approach was tested on baseline brain structural MRI scans from 429 individuals from the Alzheimer's Disease Neuroimaging Initiative (ADNI), of which 231 were CN and 198 had AD. RESULTS: The abnormal regions around the lower parts of limbic system were indicated as AD-relevant regions based on the two-sample t-test (p < 0.001), and the proposed method yielded an accuracy of 0.84 for discriminating between CN and AD. CONCLUSION: The study combined statistical and unsupervised learning methods to identify scans of people with AD. This method can detect AD-relevant regions and could be used to accurately diagnose AD; it does not require large amounts of labelled MRI scans. Our research could help in the automatic diagnosis of AD and provide a basis for diagnosing stable mild cognitive impairment (stable MCI) and progressive mild cognitive impairment (progressive MCI).

Use of Online Health Forums by People Living With Breast Cancer During the COVID-19 Pandemic: Thematic Analysis.

BACKGROUND: At the time of the UK COVID-19 lockdowns, online health forums (OHFs) were one of the relatively few remaining accessible sources of peer support for people living with breast cancer. Cancer services were heavily affected by the pandemic in many ways, including the closure of many of the customary support services. Previous studies indicate that loneliness, anxiety, distress, and depression caused by COVID-19 were common among people living with breast cancer, and this suggests that the role of OHFs in providing users with support, information, and empathy could have been of increased importance at that time. OBJECTIVE: This study aimed to examine how people living with breast cancer shared information, experiences, and emotions in an OHF during the COVID-19 pandemic. METHODS: This qualitative study thematically analyzed posts from the discussion forums of an OHF provided by the UK charity, Breast Cancer Now. We selected 1053 posts from the time of 2 UK lockdowns: March 16, 2020, to June 15, 2020 (lockdown 1), and January 6, 2021, to March 8, 2021 (lockdown 3), for analysis, from 2 of the forum's boards (for recently diagnosed people and for those undergoing chemotherapy). We analyzed the data using the original 6 steps for thematic analysis by Braun and Clarke but by following a codebook approach. Descriptive statistics for posts were also derived. RESULTS: We found that COVID-19 amplified the forum's value to its users. As patients with cancer, participants were in a situation that was "bad enough already," and the COVID-19 pandemic heightened this difficult situation. The forum's value, which was already high for the information and peer support it provided, increased because COVID-19 caused some special information needs that forum users were uniquely well placed to fulfill as people experiencing the combined effects of having breast cancer during the pandemic. The forum also met the emotional needs generated by the COVID-19 pandemic and was valued as a place where loneliness during the pandemic may be relieved and users' spirits lifted in a variety of ways specific to this period. We found some differences in use between the 2 periods and the 2 boards-most noticeable was the great fear and anxiety expressed at the beginning of lockdown 1. Both the beginning and end of lockdown periods were particularly difficult for participants, with the ends seen as potentially increasing isolation. CONCLUSIONS: The forums were an important source of support and information to their users, with their value increasing during the lockdowns for a variety of reasons. Our findings will be helpful to organizations offering OHFs and to health care workers advising people living with breast cancer about sources of support.

LMIC-PRIEST: Derivation and validation of a clinical severity score for acutely ill adults with suspected COVID-19 in a middle-income setting.

BACKGROUND: Uneven vaccination and less resilient health care systems mean hospitals in LMICs are at risk of being overwhelmed during periods of increased COVID-19 infection. Risk-scores proposed for rapid triage of need for admission from the emergency department (ED) have been developed in higher-income settings during initial waves of the pandemic. METHODS: Routinely collected data for public hospitals in the Western Cape, South Africa from the 27th August 2020 to 11th March 2022 were used to derive a cohort of 446,084 ED patients with suspected COVID-19. The primary outcome was death or ICU admission at 30 days. The cohort was divided into derivation and Omicron variant validation sets. We developed the LMIC-PRIEST score based on the coefficients from multivariable analysis in the derivation cohort and existing triage practices. We externally validated accuracy in the Omicron period and a UK cohort. RESULTS: We analysed 305,564 derivation, 140,520 Omicron and 12,610 UK validation cases. Over 100 events per predictor parameter were modelled. Multivariable analyses identified eight predictor variables retained across models. We used these findings and clinical judgement to develop a score based on South African Triage Early Warning Scores and also included age, sex, oxygen saturation, inspired oxygen, diabetes and heart disease. The LMIC-PRIEST score achieved C-statistics: 0.82 (95% CI: 0.82 to 0.83) development cohort; 0.79 (95% CI: 0.78 to 0.80) Omicron cohort; and 0.79 (95% CI: 0.79 to 0.80) UK cohort. Differences in prevalence of outcomes led to imperfect calibration in external validation. However, use of the score at thresholds of three or less would allow identification of very low-risk patients (NPV ≥0.99) who could be rapidly discharged using information collected at initial assessment. CONCLUSION: The LMIC-PRIEST score shows good discrimination and high sensitivity at lower thresholds and can be used to rapidly identify low-risk patients in LMIC ED settings.

Training and testing of a gradient boosted machine learning model to predict adverse outcome in patients presenting to emergency departments with suspected covid-19 infection in a middle-income setting.

COVID-19 infection rates remain high in South Africa. Clinical prediction models may be helpful for rapid triage, and supporting clinical decision making, for patients with suspected COVID-19 infection. The Western Cape, South Africa, has integrated electronic health care data facilitating large-scale linked routine datasets. The aim of this study was to develop a machine learning model to predict adverse outcome in patients presenting with suspected COVID-19 suitable for use in a middle-income setting. A retrospective cohort study was conducted using linked, routine data, from patients presenting with suspected COVID-19 infection to public-sector emergency departments (EDs) in the Western Cape, South Africa between 27th August 2020 and 31st October 2021. The primary outcome was death or critical care admission at 30 days. An XGBoost machine learning model was trained and internally tested using split-sample validation. External validation was performed in 3 test cohorts: Western Cape patients presenting during the Omicron COVID-19 wave, a UK cohort during the ancestral COVID-19 wave, and a Sudanese cohort during ancestral and Eta waves. A total of 282,051 cases were included in a complete case training dataset. The prevalence of 30-day adverse outcome was 4.0%. The most important features for predicting adverse outcome were the requirement for supplemental oxygen, peripheral oxygen saturations, level of consciousness and age. Internal validation using split-sample test data revealed excellent discrimination (C-statistic 0.91, 95% CI 0.90 to 0.91) and calibration (CITL of 1.05). The model achieved C-statistics of 0.84 (95% CI 0.84 to 0.85), 0.72 (95% CI 0.71 to 0.73), and 0.62, (95% CI 0.59 to 0.65) in the Omicron, UK, and Sudanese test cohorts. Results were materially unchanged in sensitivity analyses examining missing data. An XGBoost machine learning model achieved good discrimination and calibration in prediction of adverse outcome in patients presenting with suspected COVID19 to Western Cape EDs. Performance was reduced in temporal and geographical external validation.

The use and usability of EPR systems in oncology.

This paper reports preliminary findings of a study relating to the development and use of electronic patient record (EPR) systems in cancer services. The research literature demonstrates an increasing emphasis on reporting clinical outcomes and the need for effective EPR systems and high quality information, which should ultimately influence the quality of life of patients. The study is interpretative and forms part a wider research programme to define and validate CICERO, a reference model for 'Onco-EPR' systems. Preliminary conclusions from the primary study site, a leading UK cancer treatment centre, confirm the requirement for more effective Onco-EPR system design and implementation planning with emphasis on the socio-technical aspects of health informatics.

'Onco alerts' to support acute oncology services.

The National Chemotherapy Advisory Group report has recommended that all hospitals in the UK with an Emergency Department should establish an acute oncology (AO) service. Acute oncology, when implemented at a clinical network level, presents significant challenges for informatics, including the requirement for 'onco alerts' - automated notification of admission of potential cancer patients, whose diagnosis may not be recorded on the admitting hospital's IT systems. In this short paper we present a case study and describe an approach to supporting the development of AO services with cross-organisational information systems.