Developing useful early warning and prognostic scores for COVID-19

Abstract Early recognition of high-risk or deteriorating patients with COVID-19 allows timely treatment escalation and optimises allocation of scarce resources across overstretched healthcare systems. Since the late 1990s, physiological scoring systems have been used in hospital settings to provide an objective signal of clinical deterioration prompting urgent clinical review. Several early warning scores (EWS) accurately predict the need for intensive care unit admission and survival in hospitalised patients with sepsis and other acute illnesses, and their routine use is now recommended in secondary care settings in high and low income countries alike. However, there are widespread concerns that existing EWS, which place a premium on the cardiovascular instability seen in severe sepsis, may fail to identify the deteriorating COVID-19 patient. Dozens of research groups have now assessed the predictive value of existing EWS in hospitalised adults with COVID-19, and used sophisticated statistical methods to develop novel early warning and prognostic scores incorporating vital signs, laboratory tests and imaging results. However, many of these novel scores are at high risk of bias and few have been adopted in routine clinical practice. In this education and learning article, we will discuss key pitfalls of existing prognostic and EWS in hospitalised adults with COVID-19; outline promising novel scores for this patient group; and describe the ideal properties of scoring systems suitable for use in low and middle income settings

Factors associated with hospital emergency readmission and mortality rates in patients with heart failure or chronic obstructive pulmonary disease: a national observational study

Background: Heart failure (HF) and chronic obstructive pulmonary disease (COPD) lead to unplanned hospital activity, but our understanding of what drives this is incomplete. Objectives: To model patient, primary care and hospital factors associated with readmission and mortality for patients with HF and COPD, to assess the statistical performance of post-discharge emergency department (ED) attendance compared with readmission metrics and to compare all the results for the two conditions. Design: Observational study. Setting: English NHS. Participants: All patients admitted to acute non-specialist hospitals as an emergency for HF or COPD. Interventions: None. Main outcome measures: One-year mortality and 30-day emergency readmission following the patient’s first unplanned admission (‘index admission’) for HF or COPD. Data sources: Patient-level data from Hospital Episodes Statistics were combined with publicly available practice- and hospital-level data on performance, patient and staff experience and rehabilitation programme website information. Results: One-year mortality rates were 39.6% for HF and 24.1% for COPD and 30-day readmission rates were 19.8% for HF and 16.5% for COPD. Most patients were elderly with multiple comorbidities. Patient factors predicting mortality included older age, male sex, white ethnicity, prior missed outpatient appointments, (long) index length of hospital stay (LOS) and several comorbidities. Older age, missed appointments, (short) LOS and comorbidities also predicted readmission. Of the practice and hospital factors we considered, only more doctors per 10 beds [odds ratio (OR) 0.95 per doctor; p < 0.001] was significant for both cohorts for mortality, with staff recommending to friends and family (OR 0.80 per unit increase; p < 0.001) and number of general practitioners (GPs) per 1000 patients (OR 0.89 per extra GP; p = 0.004) important for COPD. For readmission, only hospital size [OR per 100 beds = 2.16, 95% confidence interval (CI) 1.34 to 3.48 for HF, and 2.27, 95% CI 1.40 to 3.66 for COPD] and doctors per 10 beds (OR 0.98; p < 0.001) were significantly associated. Some factors, such as comorbidities, varied in importance depending on the readmission diagnosis. ED visits were common after the index discharge, with 75% resulting in admission. Many predictors of admission at this visit were as for readmission minus comorbidities and plus attendance outside the day shift and numbers of admissions that hour. Hospital-level rates for ED attendance varied much more than those for readmission, but the omega statistics favoured them as a performance indicator. Limitations: Data lacked direct information on disease severity and ED attendance reasons; NHS surveys were not specific to HF or COPD patients; and some data sets were aggregated. Conclusions: Following an index admission for HF or COPD, older age, prior missed outpatient appointments, LOS and many comorbidities predict both mortality and readmission. Of the aggregated practice and hospital information, only doctors per bed and numbers of hospital beds were strongly associated with either outcome (both negatively). The 30-day ED visits and diagnosis-specific readmission rates seem to be useful performance indicators. Future work: Hospital variations in ED visits could be investigated using existing data despite coding limitations. Primary care management could be explored using individual-level linked databases. Funding: The National Institute for Health Research Health Services and Delivery Research programme

The impact of atypical intrahospital transfers on patient outcomes: a mixed methods study

The architectural design of hospitals worldwide is centred around individual departments, which require the movement of patients between wards. However, patients do not always take the simplest route from admission to discharge, but can experience convoluted movement patterns, particularly when bed availability is low. Few studies have explored the impact of these rarer, atypical trajectories. Using a mixed-method explanatory sequential study design, we firstly used three continuous years of electronic health record data prior to the Covid-19 pandemic, from 55,152 patients admitted to a London hospital network to define the ward specialities by patient type using the Herfindahl–Hirschman index. We explored the impact of ‘regular transfers’ between pairs of wards with shared specialities, ‘atypical transfers’ between pairs of wards with no shared specialities and ‘site transfers’ between pairs of wards in different hospital site locations, on length of stay, 30-day readmission and mortality. Secondly, to understand the possible reasons behind atypical transfers we conducted three focus groups and three in-depth interviews with site nurse practitioners and bed managers within the same hospital network. We found that at least one atypical transfer was experienced by 12.9% of patients. Each atypical transfer is associated with a larger increase in length of stay, 2.84 days (95% CI 2.56–3.12), compared to regular transfers, 1.92 days (95% CI 1.82–2.03). No association was found between odds of mortality, or 30-day readmission and atypical transfers after adjusting for confounders. Atypical transfers appear to be driven by complex patient conditions, a lack of hospital capacity, the need to reach specific services and facilities, and more exceptionally, rare events such as major incidents. Our work provides an important first step in identifying unusual patient movement and its impacts on key patient outcomes using a system-wide, data-driven approach. The broader impact of moving patients between hospital wards, and possible downstream effects should be considered in hospital policy and service planning

Challenges and recommendations for high quality research using electronic health records

Harnessing Real World Data is vital to improve health care in the 21st Century. Data from Electronic Health Records (EHRs) are a rich source of patient centred data, including information on the patient's clinical condition, laboratory results, diagnoses and treatments. They thus reflect the true state of health systems. However, access and utilisation of EHR data for research presents specific challenges. We assert that using data from EHRs effectively is dependent on synergy between researchers, clinicians and health informaticians, and only this will allow state of the art methods to be used to answer urgent and vital questions for patient care. We propose that there needs to be a paradigm shift in the way this research is conducted - appreciating that the research process is iterative rather than linear. We also make specific recommendations for organisations, based on our experience of developing and using EHR data in trusted research environments

Sociodemographic profiles, educational attainment and physical activity associated with The Daily Mile™ registration in primary schools in England – a national cross-sectional linkage study

Objective To examine primary school and local authority characteristics associated with registration for The Daily Mile (TDM), an active mile initiative aimed at increasing physical activity in children. Design A cross-sectional linkage study using routinely collected data. Setting All state funded primary schools in England from 2012-2018(n=15,815). Results 3,502 of all 15,815(22.1%) state funded primary schools in England were registered to do TDM, ranging from 16% in the East Midlands region to 31% in Inner London. Primary schools registered for TDM had larger mean pupil numbers compared with schools that had not registered (300 vs 269 respectively). There was a higher proportion of TDM registered schools in urban areas compared with non-urban areas. There was local authority variation in the likelihood of school registration (ICC: 0.094). After adjusting for school and local authority characteristics, schools located in a major urban conurbation (OR 1.46 (95%CI:1.24-1.71) urban vs. rural) and schools with a higher proportion of disadvantaged pupils had higher odds of being registered to the TDM (OR 1.16 (95%CI:1.02-1.33)). Area based physical activity and schools’ educational attainment was not significantly associated with registration to TDM. Conclusion One in five primary schools in England has registered for The Daily Mile since 2012. TDM appears to be a wide-reaching school based physical activity intervention that is reaching more disadvantaged primary school populations in urban areas where obesity prevalence is highest. TDM registered schools include those with both high and low educational attainment and are in areas with high and low physical activit

Sociodemographic profiles, educational attainment and physical activity associated with The Daily Mile™ registration in primary schools in England: a national cross-sectional linkage study

OBJECTIVE: To examine primary school and local authority characteristics associated with registration for The Daily Mile (TDM), an active mile initiative aimed at increasing physical activity in children. DESIGN: A cross-sectional linkage study using routinely collected data. SETTING: All state-funded primary schools in England from 2012 to 2018 (n=15,815). RESULTS: 3,502 of all 15,815 (22.1%) state-funded primary schools in England were registered to do TDM, ranging from 16% in the East Midlands region to 31% in Inner London. Primary schools registered for TDM had larger mean pupil numbers compared with schools that had not registered (300 vs 269, respectively). There was a higher proportion of TDM-registered schools in urban areas compared with non-urban areas. There was local authority variation in the likelihood of school registration (intraclass correlation coefficient: 0.094). After adjusting for school and local authority characteristics, schools located in a major urban conurbation (OR 1.46 (95% CI 1.24 to 1.71) urban vs rural) and schools with a higher proportion of disadvantaged pupils had higher odds of being registered for TDM (OR 1.16 (95% CI 1.02 to 1.33)). Area-based physical activity and schools' educational attainment were not significantly associated with registration to TDM. CONCLUSION: One in five primary schools in England has registered for TDM since 2012. TDM appears to be a wide-reaching school-based physical activity intervention that is reaching more disadvantaged primary school populations in urban areas where obesity prevalence is highest. TDM-registered schools include those with both high and low educational attainment and are in areas with high and low physical activity

Prevalence of electronic screening for sepsis in National Health Service acute hospitals in England

Sepsis is a worldwide public health problem. Rapid identification is associated with improved patient outcomes—if followed by timely appropriate treatment. Objectives Describe digital sepsis alerts (DSAs) in use in English National Health Service (NHS) acute hospitals. Methods A Freedom of Information request surveyed acute NHS Trusts on their adoption of electronic patient records (EPRs) and DSAs. Results Of the 99 Trusts that responded, 84 had an EPR. Over 20 different EPR system providers were identified as operational in England. The most common providers were Cerner (21%). System C, Dedalus and Allscripts Sunrise were also relatively common (13%, 10% and 7%, respectively). 70% of NHS Trusts with an EPR responded that they had a DSA; most of these use the National Early Warning Score (NEWS2). There was evidence that the EPR provider was related to the DSA algorithm. We found no evidence that Trusts were using EPRs to introduce data driven algorithms or DSAs able to include, for example, pre-existing conditions that may be known to increase risk. Not all Trusts were willing or able to provide details of their EPR or the underlying algorithm. Discussion The majority of NHS Trusts use an EPR of some kind; many use a NEWS2-based DSA in keeping with national guidelines. Conclusion Many English NHS Trusts use DSAs; even those using similar triggers vary and many recreate paper systems. Despite the proliferation of machine learning algorithms being developed to support early detection of sepsis, there is little evidence that these are being used to improve personalised sepsis detection

Unscheduled hospital contacts after inpatient discharge: A national observational study of COPD and heart failure patients in England

Introduction Readmissions are a recognised challenge for providers of healthcare and incur financial penalties in a growing number of countries. However, the scale of unscheduled hospital contacts including attendances at emergency departments that do not result in admission is not well known. In addition, little is known about the route to readmission for patients recently discharged from an emergency hospital stay. Methods This is an observational study of national hospital administration data for England. In this retrospective cohort study, we tracked patients for 30 days after discharge from an emergency admission for heart failure (HF) or chronic obstructive pulmonary disorder (COPD). Results The majority of patients (COPD:79%; HF:75%) had no unscheduled contact with secondary health care within 30 days of discharge. Of those who did have unscheduled contact, the most common first unscheduled contact was emergency department (ED) attendance (COPD:16%; HF:18%). A further 5% of COPD patients and 4% of HF patients were admitted for an emergency inpatient stay, but not through the ED. A small percentage of patients (COPD:<1%, HF:2%) died without any known contact with secondary care. ED conversion rates at first attendance for both COPD and HF were high: 75% and 79% respectively. A quarter of patients who were not admitted during this first ED attendance attended the ED again within the 30-day follow-up period, and around half (COPD:56%; HF:63%) of these were admitted at this point. Patients who live alone, had an index admission which included an overnight stay and were comorbid had higher odds of being admitted through the ED than via other routes. Conclusion While the majority of patients did not have unscheduled contact with secondary care in the 30 days after index discharge, many patients attended the ED, often multiple times, and many were admitted to hospital, not always via the ED. More frail patients were more likely to be admitted through the ED, suggesting a possible area of focus as discharge bundles are developed

Views and uses of sepsis digital alerts in national health service trusts in England: qualitative study with health care professionals

Background: Sepsis is a common cause of serious illness and death. Sepsis management remains challenging and suboptimal. To support rapid sepsis diagnosis and treatment, screening tools have been embedded into hospital digital systems to appear as digital alerts. The implementation of digital alerts to improve the management of sepsis and deterioration is a complex intervention that has to fit with team workflow and the views and practices of hospital staff. Despite the importance of human decision-making and behavior in optimal implementation, there are limited qualitative studies that explore the views and experiences of health care professionals regarding digital alerts as sepsis or deterioration computerized clinician decision support systems (CCDSSs). Objective: This study aims to explore the views and experiences of health care professionals on the use of sepsis or deterioration CCDSSs and to identify barriers and facilitators to their implementation and use in National Health Service (NHS) hospitals. Methods: We conducted a qualitative, multisite study with unstructured observations and semistructured interviews with health care professionals from emergency departments, outreach teams, and intensive or acute units in 3 NHS hospital trusts in England. Data from both interviews and observations were analyzed together inductively using thematic analysis. Results: A total of 22 health care professionals were interviewed, and 12 observation sessions were undertaken. A total of four themes regarding digital alerts were identified: (1) support decision-making as nested in electronic health records, but never substitute professionals’ knowledge and experience; (2) remind to take action according to the context, such as the hospital unit and the job role; (3) improve the alerts and their introduction, by making them more accessible, easy to use, not intrusive, more accurate, as well as integrated across the whole health care system; and (4) contextual factors affecting views and use of alerts in the NHS trusts. Digital alerts are more optimally used in general hospital units with a lower senior decision maker:patient ratio and by health care professionals with experience of a similar technology. Better use of the alerts was associated with quality improvement initiatives and continuous sepsis training. The trusts’ features, such as the presence of a 24/7 emergency outreach team, good technological resources, and staffing and teamwork, favored a more optimal use. Conclusions: Trust implementation of sepsis or deterioration CCDSSs requires support on multiple levels and at all phases of the intervention, starting from a prego-live analysis addressing organizational needs and readiness. Advancements toward minimally disruptive and smart digital alerts as sepsis or deterioration CCDSSs, which are more accurate and specific but at the same time scalable and accessible, require policy changes and investments in multidisciplinary research