Enhancing clinical data retrieval with Smart Watchers: a NiFi-based ETL pipeline for Elasticsearch queries.

BACKGROUND: The aim is to develop and deploy an automated clinical alert system to enhance patient care and streamline healthcare operations. Structured and unstructured data from multiple sources are used to generate near real-time alerts for specific clinical scenarios, with an additional goal to improve clinical decision-making through accuracy and reliability. METHODS: The automated clinical alert system, named Smart Watchers, was developed using Apache NiFi and Python scripts to create flexible data processing pipelines and customisable clinical alerts. A comparative analysis between Smart Watchers and the legacy Elastic Watchers was conducted to evaluate performance metrics such as accuracy, reliability, and scalability. The evaluation involved measuring the time taken for manual data extraction through the electronic patient record (EPR) front-end and comparing it with the automated data extraction process using Smart Watchers. RESULTS: Deployment of Smart Watchers showcased a consistent time savings between 90% to 98.67% compared to manual data extraction through the EPR front-end. The results demonstrate the efficiency of Smart Watchers in automating data extraction and alert generation, significantly reducing the time required for these tasks when compared to manual methods in a scalable manner. CONCLUSIONS: The research underscores the utility of employing an automated clinical alert system, and its portability facilitated its use across multiple clinical settings. The successful implementation and positive impact of the system lay a foundation for future technological innovations in this rapidly evolving field.

The burden of hyperkalaemia on hospital healthcare resources.

Hyperkalaemia is associated with prolonged hospital admission and worse mortality. Hyperkalaemia may also necessitate clinical consults, therapies for hyperkalaemia and high-dependency bed utilisation. We evaluated the 'hidden' human and organisational resource utilisation for hyperkalaemia in hospitalised patients. This was a single-centre, observational cohort study (Jan 2017-Dec 2020) at a tertiary-care hospital. The CogStack system (data processing and analytics platform) was used to search unstructured and structured data from individual patient records. Association between potassium and death was modelled using cubic spline regression, adjusted for age, sex, and comorbidities. Cox proportional hazards estimated the hazard of death compared with normokalaemia (3.5-5.0 mmol/l). 129,172 patients had potassium measurements in the emergency department. Incidence of hyperkalaemia was 85.7 per 1000. There were 49,011 emergency admissions. Potassium > 6.5 mmol/L had 3.9-fold worse in-hospital mortality than normokalaemia. Chronic kidney disease was present in 21% with potassium 5-5.5 mmol/L and 54% with potassium > 6.5 mmol/L. For diabetes, it was 20% and 32%, respectively. Of those with potassium > 6.5 mmol/L, 29% had nephrology review, and 13% critical care review; in this group 22% transferred to renal wards and 8% to the critical care unit. Dialysis was used in 39% of those with peak potassium > 6.5 mmol/L. Admission hyperkalaemia and hypokalaemia were independently associated with reduced likelihood of hospital discharge. Hyperkalaemia is associated with greater in-hospital mortality and reduced likelihood of hospital discharge. It necessitated significant utilisation of nephrology and critical care consultations and greater likelihood of patient transfer to renal and critical care.

Premature mortality and disparities in kidney healthcare for people with chronic kidney disease and severe mental health difficulties.

BACKGROUND: People with severe mental health difficulties, including schizophrenia, bipolar disorder and psychosis, have higher risk of chronic kidney disease (CKD). Little was known regarding clinical outcomes and utilisation of kidney care for people with CKD and severe mental health difficulties. METHODS: We conducted a retrospective cohort analysis of individuals with CKD attending a tertiary renal unit in London, between 2006 and 2019. Individuals with severe mental health difficulty diagnoses were identified, and differences between those with and without severe mental health difficulties were analysed. RESULTS: Of the 5105 individuals with CKD, 112 (2.2%) had a recorded severe mental health difficulty diagnosis. The mean lifespan of those with severe mental health difficulties was 13.1 years shorter than those without severe mental health difficulties, t(1269) = 5.752, p < 0.001. People with severe mental health difficulties had more advanced CKD at their first nephrology appointment. There were no statistically significant differences between groups in the rates of kidney failure, age at onset of kidney failure, or time elapsed between first appointment and death/kidney failure. The number of inpatient admissions was similar between groups, but those with severe mental health difficulties had higher rates of emergency and ICU admissions. Among individuals on renal replacement therapy (RRT), those with severe mental health difficulties were less likely to receive a kidney transplant and peritoneal dialysis. For patients receiving haemodialysis, those with severe mental health difficulties had a higher proportion of shortened sessions, greater mean weight loss during sessions, and a higher proportion of serum potassium and phosphate levels outside normal ranges. CONCLUSIONS: Findings illustrate a number of disparities in kidney healthcare between people with and without severe mental health difficulties, underscoring the need for interventions which prevent premature mortality and improve kidney care for this population.

Diagnostic accuracy, clinical characteristics, and prognostic differences of patients with acute myocarditis according to inclusion criteria.

INTRODUCTION: The diagnosis of acute myocarditis (AM) is complex due to its heterogeneity and typically is defined by either Electronic Healthcare Records (EHRs) or advanced imaging and endomyocardial biopsy, but there is no consensus. We aimed to investigate the diagnostic accuracy of these approaches for AM. METHODS: Data on ICD 10th Revision(ICD-10) codes corresponding to AM were collected from two hospitals and compared to CMR-confirmed or clinically suspected(CS) AM cases with respect to diagnostic accuracy, clinical characteristics, and all-cause mortality. Next, we performed a review of published AM studies according to inclusion criteria. RESULTS: We identified 291 unique admissions with ICD-10 codes corresponding to AM in the first three diagnostic positions. The positive predictive value(PPV) of ICD-10 codes for CMR-confirmed or CS-AM was 36%, and patients with CMR-confirmed or CS AM had a lower all-cause mortality than those with a refuted diagnosis (P = 0.019). Using an unstructured approach, patients with CMR-confirmed and CS AM had similar demographics, comorbidity profiles and survival over a median follow-up of 52 months (P = 0.72). Our review of the literature confirmed our findings. Outcomes for patients included in studies using CMR-confirmed criteria were favourable compared to studies with EMB-confirmed AM cases. CONCLUSION: ICD-10 codes have poor accuracy in identification of AM cases and should be used with caution in clinical research. There are important differences in management and outcomes of patients according to the selection criteria used to diagnose AM. Potential selection biases must be considered when interpreting AM cohorts and requires standardisation of inclusion criteria for AM studies.

Prognostic relevance of demographic factors in cardiac magnetic resonance-proven acute myocarditis: A cohort study.

Aim: Acute myocarditis (AM) is a heterogeneous condition with variable estimates of survival. Contemporary criteria for the diagnosis of clinically suspected AM enable non-invasive assessment, resulting in greater sensitivity and more representative cohorts. We aimed to describe the demographic characteristics and long-term outcomes of patients with AM diagnosed using non-invasive criteria. Methods and results: A total of 199 patients with cardiac magnetic resonance (CMR)-confirmed AM were included. The majority (n = 130, 65%) were male, and the average age was 39 ± 16 years. Half of the patients were White (n = 99, 52%), with the remainder from Black and Minority Ethnic (BAME) groups. The most common clinical presentation was chest pain (n = 156, 78%), with smaller numbers presenting with breathlessness (n = 25, 13%) and arrhythmias (n = 18, 9%). Patients admitted with breathlessness were sicker and more often required inotropes, steroids, and renal replacement therapy (p < 0.001, p < 0.001, and p = 0.01, respectively). Over a median follow-up of 53 (IQR 34-76) months, 11 patients (6%) experienced an adverse outcome, defined as a composite of all-cause mortality, resuscitated cardiac arrest, and appropriate implantable cardioverter defibrillator (ICD) therapy. Patients in the arrhythmia group had a worse prognosis, with a nearly sevenfold risk of adverse events [hazard ratio (HR) 6.97; 95% confidence interval (CI) 1.87-26.00, p = 0.004]. Sex and ethnicity were not significantly associated with the outcome. Conclusion: AM is highly heterogeneous with an overall favourable prognosis. Three-quarters of patients with AM present with chest pain, which is associated with a benign prognosis. AM presenting with life-threatening arrhythmias is associated with a higher risk of adverse events.

Natural language word embeddings as a glimpse into healthcare language and associated mortality surrounding end of life.

OBJECTIVES: To clarify real-world linguistic nuances around dying in hospital as well as inaccuracy in individual-level prognostication to support advance care planning and personalised discussions on limitation of life sustaining treatment (LST). DESIGN: Retrospective cross-sectional study of real-world clinical data. SETTING: Secondary care, urban and suburban teaching hospitals. PARTICIPANTS: All inpatients in 12-month period from 1 October 2018 to 30 September 2019. METHODS: Using unsupervised natural language processing, word embedding in latent space was used to generate phrase clusters with most similar semantic embeddings to 'Ceiling of Treatment' and their prognostication value. RESULTS: Word embeddings with most similarity to 'Ceiling of Treatment' clustered around phrases describing end-of-life care, ceiling of care and LST discussions. The phrases have differing prognostic profile with the highest 7-day mortality in the phrases most explicitly referring to end of life-'Withdrawal of care' (56.7%), 'terminal care/end of life care' (57.5%) and 'un-survivable' (57.6%). CONCLUSION: Vocabulary used at end-of-life discussions are diverse and has a range of associations to 7-day mortality. This highlights the importance of correct application of terminology during LST and end-of-life discussions.

Diarrhoea and preadmission antibiotic exposure in COVID-19: a retrospective cohort study of 1153 hospitalised patients.

OBJECTIVE: The aims of this study were to describe community antibiotic prescribing patterns in individuals hospitalised with COVID-19, and to determine the association between experiencing diarrhoea, stratified by preadmission exposure to antibiotics, and mortality risk in this cohort. DESIGN/METHODS: Retrospective study of the index presentations of 1153 adult patients with COVID-19, admitted between 1 March 2020 and 29 June 2020 in a South London NHS Trust. Data on patients' medical history (presence of diarrhoea, antibiotic use in the previous 14 days, comorbidities); demographics (age, ethnicity, and body mass index); and blood test results were extracted. Time to event modelling was used to determine the risk of mortality for patients with diarrhoea and/or exposure to antibiotics. RESULTS: 19.2% of the cohort reported diarrhoea on presentation; these patients tended to be younger, and were less likely to have recent exposure to antibiotics (unadjusted OR 0.64, 95% CI 0.42 to 0.97). 19.1% of the cohort had a course of antibiotics in the 2 weeks preceding admission; this was associated with dementia (unadjusted OR 2.92, 95% CI 1.14 to 7.49). After adjusting for confounders, neither diarrhoea nor recent antibiotic exposure was associated with increased mortality risk. However, the absence of diarrhoea in the presence of recent antibiotic exposure was associated with a 30% increased risk of mortality. CONCLUSION: Community antibiotic use in patients with COVID-19, prior to hospitalisation, is relatively common, and absence of diarrhoea in antibiotic-exposed patients may be associated with increased risk of mortality. However, it is unclear whether this represents a causal physiological relationship or residual confounding.