Background:
Previous studies showed increasing number of children with a life-limiting or life-threatening condition who may benefit from input from pediatric palliative care services.
Aim:
To ...estimate the current prevalence of children with a life-limiting condition and to model future prevalence of this population.
Design:
Observational study using national inpatient hospital data. A population-based approach utilizing ethnic specific population projections was used to estimate future prevalence.
Setting/participants:
All children aged 0–19 years with a life-limiting condition diagnostic code recorded in Hospital Episodes Statistics data in England from 2000/01 to 2017/18.
Results:
Data on 4,543,386 hospital episodes for 359,634 individuals were included. The prevalence of children with a life-limiting condition rose from 26.7 per 10,000 (95%CI 26.5–27.0) in 2001/02 to 66.4 per 10,000 (95% CI: 66.0–66.8) in 2017/18. Using a more restricted definition of a life-limiting condition reduced the prevalence from 66.4 to 61.1 per 10,000 (95%CI 60.7–61.5) in 2017/18. Highest prevalence was in the under 1-year age group at 226.5 per 10,000 and children with a congenital abnormality had the highest prevalence (27.2 per 10,000 (95%CI: 26.9–27.5)).
The prevalence was highest among the most deprived group and in children of Pakistani origin.
Predicted future prevalence of life-limiting conditions ranged from 67.0 (95%CI 67.7–66.3) to 84.22 (95%CI 78.66–90.17) per 10,000 by 2030.
Conclusions:
The prevalence of children with a life-limiting or life-threatening condition in England has risen over the last 17 years and is predicted to increase. Future data collections must include the data required to assess the complex health and social care needs of these children.
Improved survival has led to increasing numbers of children with life-limiting conditions transitioning to adult healthcare services. There are concerns that transition may lead to a reduction in ...care quality and increases in emergency care. This review explores evidence for differences in health or social care use post- versus pre-transition to adult services.
MEDLINE, EMBASE, CINAHL, PsychINFO and Social Science Citation Index were searched. Studies published in English since 1990 including individuals with any life-limiting condition post- and pre-transition and reporting a health or social care use outcome were included. Data were extracted and quality assessed by one reviewer with 30% checked by an independent reviewer.
Nineteen papers (18 studies) met the inclusion criteria. There was evidence for both increases and decreases (post- versus pre-transition) in outpatient attendance, inpatient admissions, inpatient bed days and health service costs; for increases in Emergency Department visits and for decreases in individuals receiving physiotherapy.
Evidence for changes in healthcare use post- versus pre-transition is mixed and conflicting, although there is evidence for an increase in Emergency Department visits and a reduction in access to physiotherapy. More high-quality research is needed to better link changes in care to the transition.
Evidence for changes in healthcare use associated with transition to adult services is conflicting. Emergency Department visits increase and access to physiotherapy decreases at transition. There are marked differences between care patterns in the United States and Canada.
OBJECTIVE:To compare the ability of medical emergency team criteria and the National Early Warning Score to discriminate cardiac arrest, unanticipated ICU admission and death within 24 hours of a ...vital signs measurement, and to quantify the associated workload.
DESIGN:Retrospective cohort study.
SETTING:A large U.K. National Health Service District General Hospital.
PATIENTS:Adults hospitalized from May 25, 2011, to December 31, 2013.
INTERVENTIONS:None.
MEASUREMENTS AND MAIN RESULTS:We applied the National Early Warning Score and 44 sets of medical emergency team criteria to a database of 2,245,778 vital signs sets (103,998 admissions). The National Early Warning Score’s performance was assessed using the area under the receiver-operating characteristic curve and compared with sensitivity/specificity for different medical emergency team criteria. Area under the receiver-operating characteristic curve (95% CI) for the National Early Warning Score for the combined outcome (i.e., death, cardiac arrest, or unanticipated ICU admission) was 0.88 (0.88–0.88). A National Early Warning Score value of 7 had sensitivity/specificity values of 44.5% and 97.4%, respectively. For the 44 sets of medical emergency team criteria studied, sensitivity ranged from 19.6% to 71.2% and specificity from 71.5% to 98.5%. For all outcomes, the position of the National Early Warning Score receiver-operating characteristic curve was above and to the left of all medical emergency team criteria points, indicating better discrimination. Similarly, the positions of all medical emergency team criteria points were above and to the left of the National Early Warning Score efficiency curve, indicating higher workloads (trigger rates).
CONCLUSIONS:When medical emergency team systems are compared to a National Early Warning Score value of greater than or equal to 7, some medical emergency team systems have a higher sensitivity than National Early Warning Score values of greater than or equal to 7. However, all of these medical emergency team systems have a lower specificity and would generate greater workloads.
ObjectivesTo better understand the complexity and healthcare needs of children and young people in Wales with life-limiting or life threatening conditions to better plan and target healthcare ...services. Previous attempts to quantify complexity have required primary data collection; this is not feasible at scale, use of existing data is preferred.
MethodsRoutinely collected healthcare and administrative data were linked: primary care data, hospital care data sets, cancer and congenital anomaly registries, paediatric intensive care audit data and death records. Children and young people with life-limiting conditions were identified using a previously developed diagnostic framework. Previous work on conceptualising medical complexity across eight domains was operationalised for the first time using the wide range of available data, with scores across five domains and a total complexity score. The relationship between the complexity score, healthcare use, stage of condition and category of condition was explored.
ResultsChildren and young people with life-limiting conditions showed the full range of medical complexity scores, from zero to five, with distributions varying across age groups with increasing complexity at greater ages. Distributions also varied across categories of condition, with congenital and oncology conditions, although among the most prevalent, exhibiting lower medical complexity. Nonetheless, all conditions showed a range of complexities – there were no conditions for which all individuals were either high or low complexity. Complexity scores were correlated with stage of condition and healthcare use and may be used to identify groups likely to have higher healthcare demand or greater risk of clinical instability. While life-limiting conditions were more prevalent in areas of higher deprivation, there was no association between deprivation and medical complexity.
ConclusionAssessment of medical complexity from routinely-collected data can be useful in better understanding a population and in targeting and planning care, without requiring additional data collection. This can help to design resilient services that prepare for changing needs and aid targeting of limited resources.
ObjectivesTo estimate point of transition from paediatric to adult healthcare from routinely collected healthcare records and to use this to compare emergency care use pre- and post transition for ...young people with life-limiting conditions.
ApproachRoutinely collected healthcare records were obtained from the Clinical Practice Research Datalink. These included linked primary care and hospital (inpatient, outpatient and A&E) records and death and deprivation data. The data were used to identify young people (12-23 years)with life-limiting conditions, diabetes and no long term conditions. Methods were developed to estimate point of transition from paediatric to adult care by classifying treatment specialties recorded in inpatient and outpatient care as paediatric or adult. These were compared and a favoured method selected. Emergency hospital care use was then compared, pre- and post-transition to adult care for the three groups.
ResultsThe last inpatient or outpatient record classified as paediatric care was chosen as the transition point. Simulation showed that this had the potential for far greater sensitivity to changes at transition (~20% difference in detected effect size) than using a simple age cut-off. Application of the method to the data showed significant increases in emergency inpatient admissions (by 29%, 95% confidence interval 14-46%) and A&E visits (by 24%, 95% confidence interval 12-38%) post- compared to pre-transition in the life-limiting conditions group, but no increases for the diabetes or no long term conditions groups, suggesting that transition has little effect for these groups.
ConclusionLinked, routinely collected healthcare records, combined with estimating transition point from the data, provide a more sensitive method for detecting changes at transition with reduced risk of misclassification bias. There is an increase in emergency care after transition, with negative effects on young people, families and cost implications for providers.
Abstract Introduction The Royal College of Physicians (RCPL) National Early Warning Score (NEWS) escalates care to a doctor at NEWS values of ≥5 and when the score for any single vital sign is 3. ...Methods We calculated the 24-h risk of serious clinical outcomes for vital signs observation sets with NEWS values of 3, 4 and 5, separately determining risks when the score did/did not include a single score of 3. We compared workloads generated by the RCPL's escalation protocol and for aggregate NEWS value alone. Results Aggregate NEWS values of 3 or 4 ( n = 142,282) formed 15.1% of all vital signs sets measured; those containing a single vital sign scoring 3 ( n = 36,207) constituted 3.8% of all sets. Aggregate NEWS values of either 3 or 4 with a component score of 3 have significantly lower risks (OR: 0.26 and 0.53) than an aggregate value of 5 (OR: 1.0). Escalating care to a doctor when any single component of NEWS scores 3 compared to when aggregate NEWS values ≥5, would have increased doctors’ workload by 40% with only a small increase in detected adverse outcomes from 2.99 to 3.08 per day (a 3% improvement in detection). Conclusions The recommended NEWS escalation protocol produces additional work for the bedside nurse and responding doctor, disproportionate to a modest benefit in increased detection of adverse outcomes. It may have significant ramifications for efficient staff resource allocation, distort patient safety focus and risk alarm fatigue. Our findings suggest that the RCPL escalation guidance warrants review.
Abstract Aim of study : To compare the performance of a human-generated, trial and error-optimised early warning score (EWS), i.e., National Early Warning Score (NEWS), with one generated entirely ...algorithmically using Decision Tree (DT) analysis. Materials and methods We used DT analysis to construct a decision-tree EWS (DTEWS) from a database of 198,755 vital signs observation sets collected from 35,585 consecutive, completed acute medical admissions. We evaluated the ability of DTEWS to discriminate patients at risk of cardiac arrest, unanticipated intensive care unit admission or death, each within 24 h of a given vital signs observation. We compared the performance of DTEWS and NEWS using the area under the receiver-operating characteristic (AUROC) curve. Results The structures of DTEWS and NEWS were very similar. The AUROC (95% CI) for DTEWS for cardiac arrest, unanticipated ICU admission, death, and any of the outcomes, all within 24 h, were 0.708 (0.669–0.747), 0.862 (0.852–0.872), 0.899 (0.892–0.907), and 0.877 (0.870–0.883), respectively. Values for NEWS were 0.722 (0.685–0.759) cardiac arrest, 0.857 (0.847–0.868) unanticipated ICU admission}, 0.894 (0.887–0.902) death, and 0.873 (0.866–0.879) any outcome. Conclusions The decision-tree technique independently validates the composition and weightings of NEWS. The DT approach quickly provided an almost identical EWS to NEWS, although one that admittedly would benefit from fine-tuning using clinical knowledge. We believe that DT analysis could be used to quickly develop candidate models for disease-specific EWSs, which may be required in future.
Background:
The number of children with life-limiting conditions in England is known to be increasing, which has been attributed in part to increased survival times. Consequently, more of these young ...people will reach ages at which they start transitioning to adult healthcare (14-19 years). However, no research exists that quantifies the number of young people with life-limiting conditions in England reaching transition ages or their medical complexity, both essential data for good service planning.
Methods:
National hospital data in England (Hospital Episode Statistics) from NHS Digital were used to identify the number of young people aged 14-19 years from 2012/13 to 2018/19 with life-limiting conditions diagnosed in childhood. The data were assessed for indicators of medical complexity: number of conditions, number of main specialties of consultants involved, number of hospital admissions and Accident & Emergency Department visits, length of stay, bed days and technology dependence (gastrostomies, tracheostomies). Overlap between measures of complexity was assessed.
Results:
The number of young people with life-limiting conditions has increased rapidly over the study period, from 20363 in 2012/13 to 34307 in 2018/19. There was evidence for increased complexity regarding the number of conditions and number of distinct main specialties of consultants involved in care, but limited evidence of increases in average healthcare use per person or increased technology dependence. The increasing size of the group meant that healthcare use increased overall. There was limited overlap between measures of medical complexity.
Conclusions:
The number of young people with life-limiting conditions reaching ages at which transition to adult healthcare should take place is increasing rapidly. Healthcare providers will need to allocate resources to deal with increasing healthcare demands and greater complexity. The transition to adult healthcare must be managed well to limit impacts on healthcare resource use and improve experiences for young people and their families.
Abstract Introduction Sicker patients generally have more vital sign assessments, particularly immediately before an adverse outcome, and especially if the vital sign monitoring schedule is driven by ...an early warning score (EWS) value. This lack of independence could influence the measured discriminatory performance of an EWS. Methods We used a population of 1564,143 consecutive vital signs observation sets collected as a routine part of patients’ care. We compared 35 published EWSs for their discrimination of the risk of death within 24 h of an observation set using (1) all observations in our dataset, (2) one observation per patient care episode, chosen at random and (3) one observation per patient care episode, chosen as the closest to a randomly selected point in time in each episode. We compared the area under the ROC curve (AUROC) as a measure of discrimination for each of the 35 EWSs under each observation selection method and looked for changes in their rank order. Results There were no significant changes in rank order of the EWSs based on AUROC between the different observation selection methods, except for one EWS that included age among its components. Whichever method of observation selection was used, the National Early Warning Score (NEWS) showed the highest discrimination of risk of death within 24 h. AUROCs were higher when only one observation set was used per episode of care (significantly higher for many EWSs, including NEWS). Conclusions Vital sign measurements can be treated as if they are independent – multiple observations can be used from each episode of care – when comparing the performance and ranking of EWSs, provided no EWS includes age.
Abstract Aim of study To build an early warning score (EWS) based exclusively on routinely undertaken laboratory tests that might provide early discrimination of in-hospital death and could be easily ...implemented on paper. Materials and methods Using a database of combined haematology and biochemistry results for 86,472 discharged adult patients for whom the admission specialty was Medicine, we used decision tree (DT) analysis to generate a laboratory decision tree early warning score (LDT-EWS) for each gender. LDT-EWS was developed for a single set ( n = 3496) (Q1 ) and validated in 22 other discrete sets each of three months long (Q2 , Q3 …Q23 ) (total n = 82,976; range of n = 3428 to 4093) by testing its ability to discriminate in-hospital death using the area under the receiver-operating characteristic (AUROC) curve. Results The data generated slightly different models for male and female patients. The ranges of AUROC values (95% CI) for LDT-EWS with in-hospital death as the outcome for the validation sets Q2 –Q23 were: 0.755 (0.727–0.783) (Q16 ) to 0.801 (0.776–0.826) all patients combined, n = 82,976; 0.744 (0.704–0.784, Q16) to 0.824 (0.792–0.856, Q2) 39,591 males; and 0.742 (0.707–0.777, Q10) to 0.826 (0.796–0.856, Q12) 43,385 females. Conclusions This study provides evidence that the results of commonly measured laboratory tests collected soon after hospital admission can be represented in a simple, paper-based EWS (LDT-EWS) to discriminate in-hospital mortality. We hypothesise that, with appropriate modification, it might be possible to extend the use of LDT-EWS throughout the patient's hospital stay.
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