Validating a methodology to measure frailty syndromes at hospital level utilising administrative data.

BACKGROUND: Identifying older people with clinical frailty, reliably and at scale, is a research priority. We measured frailty in older people using a novel methodology coding frailty syndromes on routinely collected administrative data, developed on a national English secondary care population, and explored its performance of predicting inpatient mortality and long length of stay at a single acute hospital. METHODOLOGY: We included patient spells from Secondary User Service (SUS) data for those ≥65 years with attendance to the emergency department or admission to West Middlesex University Hospital between 01 July 2016 to 01 July 2017. We created eight groups of frailty syndromes using diagnostic coding groups. We used descriptive statistics and logistic regression to explore performance of diagnostic coding groups for the above outcomes. RESULTS: We included 17,199 patient episodes in the analysis. There was at least one frailty syndrome present in 7,004 (40.7%) patient episodes. The resultant model had moderate discrimination for inpatient mortality (area under the receiver operating characteristic curve (AUC) 0.74; 95% confidence interval (CI) 0.72-0.76) and upper quartile length of stay (AUC 0.731; 95% CI 0.722-0.741). There was good negative predictive value for inpatient mortality (98.1%). CONCLUSIONS: Coded frailty syndromes significantly predict outcomes. Model diagnostics suggest the model could be used for screening of elderly patients to optimise their care

Using geographical information systems and cartograms as a health service quality improvement tool

Introduction: Disease prevalence can be spatially analysed to provide support for service implementation and health care planning, these analyses often display geographic variation. A key challenge is to communicate these results to decision makers, with variable levels of Geographic Information Systems (GIS) knowledge, in a way that represents the data and allows for comprehension. The present research describes the combination of established GIS methods and software tools to produce a novel technique of visualising disease admissions and to help prevent misinterpretation of data and less optimal decision making. The aim of this paper is to provide a tool that supports the ability of decision makers and service teams within health care settings to develop services more efficiently and better cater to the population; this tool has the advantage of information on the position of populations, the size of populations and the severity of disease. Methods: A standard choropleth of the study region, London, is used to visualise total emergency admission values for Chronic Obstructive Pulmonary Disease and bronchiectasis using ESRI's ArcGIS software. Population estimates of the Lower Super Output Areas (LSOAs) are then used with the ScapeToad cartogram software tool, with the aim of visualising geography at uniform population density. An interpolation surface, in this case ArcGIS' spline tool, allows the creation of a smooth surface over the LSOA centroids for admission values on both standard and cartogram geographies. The final product of this research is the novel Cartogram Interpolation Surface (CartIS). Results: The method provides a series of outputs culminating in the CartIS, applying an interpolation surface to a uniform population density. The cartogram effectively equalises the population density to remove visual bias from areas with a smaller population, while maintaining contiguous borders. CartIS decreases the number of extreme positive values not present in the underlying data as can be found in interpolation surfaces. Discussion: This methodology provides a technique for combining simple GIS tools to create a novel output, CartIS, in a health service context with the key aim of improving visualisation communication techniques which highlight variation in small scale geographies across large regions. CartIS more faithfully represents the data than interpolation, and visually highlights areas of extreme value more than cartograms, when either is used in isolation. © 2014 The Authors

Parents’ Experiences of Communication in neonatal care (PEC): a neonatal survey refined for real-time parent feedback

Objective Assessing parent experiences of neonatal services can help improve quality of care; however, there is no formally evaluated UK instrument available to assess this prospectively. Our objective was to refine an existing retrospective survey for ‘real-time’ feedback. Methods Co-led by a parent representative, we recruited a convenience sample of parents of infants in a London tertiary neonatal unit. Our steering group selected questions from the existing retrospective 61-question Picker survey (2014), added and revised questions assessing communication and parent involvement. We established face validity, ensuring questions adequately captured the topic, conducted parent cognitive interviews to evaluate parental understanding of questions,and adapted the survey in three revision cycles. We evaluated survey performance. Results The revised Parents’ Experiences of Communication in Neonatal Care (PEC) survey contains 28 questions (10 new) focusing on communication and parent involvement. We cognitively interviewed six parents, and 67 parents completed 197 PEC surveys in the survey performance evaluation. Missing entries exceeded 5% for nine questions; we removed one and format-adjusted the rest as they had performed well during cognitive testing. There was strong inter-item correlation between two question pairs; however, all were retained as they individually assessed important concepts. Conclusion Revised from the original 61-question Picker survey, the 28-question PEC survey is the first UK instrument formally evaluated to assess parent experience while infants are still receiving neonatal care. Developed with parents, it focuses on communication and parent involvement, enabling continuous assessment and iterative improvement of family-centred interventions in neonatal care

Finding consensus on Frailty Assessment in Acute Care through Delphi method

Objective: We seek to address gaps in knowledge and agreement around optimal frailty assessment in the acute medical care setting. Frailty is a common term describing older persons who are at increased risk of developing multi-morbidity, disability, institutionalisation, and death. Consensus has not been reached on the practical implementation of this concept to assess clinically and manage older persons in the acute care setting. Design: Modified Delphi, via electronic questionnaire. Questions included ranking items that best recognise frailty, optimal timing, location, and contextual elements of a successful tool. Intra-Class Correlation Coefficients for overall levels of agreement; with consensus and stability tested by two-way ANOVA with absolute agreement and Fisher's Exact Test. Participants: A panel of national experts (academics, front-line clinicians, and specialist charities) were invited to electronic correspondence. Results: Variables reflecting accumulated deficit and high resource utilisation were perceived by participants as the most useful indicators of frailty in the acute care setting. The Acute Medical Unit and Care of the older Persons Ward were perceived as optimum settings for frailty assessment. "Clinically meaningful and relevant", "simple (easy to use)" and "Accessible by multidisciplinary team" were perceived as characteristics of a successful frailty assessment tool in the acute care setting. No agreement was reached on optimal timing, number of variables, and organisational structures. Conclusions: This study is a first step in developing consensus for a clinically relevant frailty assessment model for the acute care setting, providing content validation, and illuminating contextual requirements. Testing on clinical datasets is a research priority

Quantifying the prevalence of frailty in English hospitals

OBJECTIVES: Population ageing has been associated with an increase in comorbid chronic disease, functional dependence, disability and associated higher health care costs. Frailty Syndromes have been proposed as a way to define this group within older persons. We explore whether frailty syndromes are a reliable methodology to quantify clinically significant frailty within hospital settings, and measure trends and geospatial variation using English secondary care data set Hospital Episode Statistics (HES). SETTING: National English Secondary Care Administrative Data HES. PARTICIPANTS: All 50 540 141 patient spells for patients over 65 years admitted to acute provider hospitals in England (January 2005—March 2013) within HES. PRIMARY AND SECONDARY OUTCOME MEASURES: We explore the prevalence of Frailty Syndromes as coded by International Statistical Classification of Diseases, Injuries and Causes of Death (ICD-10) over time, and their geographic distribution across England. We examine national trends for admission spells, inpatient mortality and 30-day readmission. RESULTS: A rising trend of admission spells was noted from January 2005 to March 2013(daily average admissions for month rising from over 2000 to over 4000). The overall prevalence of coded frailty is increasing (64 559 spells in January 2005 to 150 085 spells by Jan 2013). The majority of patients had a single frailty syndrome coded (10.2% vs total burden of 13.9%). Cognitive impairment and falls (including significant fracture) are the most common frailty syndromes coded within HES. Geographic variation in frailty burden was in keeping with known distribution of prevalence of the English elderly population and location of National Health Service (NHS) acute provider sites. Overtime, in-hospital mortality has decreased (>65 years) whereas readmission rates have increased (esp.>85 years). CONCLUSIONS: This study provides a novel methodology to reliably quantify clinically significant frailty. Applications include evaluation of health service improvement over time, risk stratification and optimisation of services

Developing and validating a risk prediction model for acute care based on frailty syndromes

OBJECTIVES: Population ageing may result in increased comorbidity, functional dependence and poor quality of life. Mechanisms and pathophysiology underlying frailty have not been fully elucidated, thus absolute consensus on an operational definition for frailty is lacking. Frailty scores in the acute medical care setting have poor predictive power for clinically relevant outcomes. We explore the utility of frailty syndromes (as recommended by national guidelines) as a risk prediction model for the elderly in the acute care setting. SETTING: English Secondary Care emergency admissions to National Health Service (NHS) acute providers. PARTICIPANTS: There were N=2 099 252 patients over 65 years with emergency admission to NHS acute providers from 01/01/2012 to 31/12/2012 included in the analysis. PRIMARY AND SECONDARY OUTCOME MEASURES: Outcomes investigated include inpatient mortality, 30-day emergency readmission and institutionalisation. We used pseudorandom numbers to split patients into train (60%) and test (40%). Receiver operator characteristic (ROC) curves and ordering the patients by deciles of predicted risk was used to assess model performance. Using English Hospital Episode Statistics (HES) data, we built multivariable logistic regression models with independent variables based on frailty syndromes (10th revision International Statistical Classification of Diseases, Injuries and Causes of Death (ICD-10) coding), demographics and previous hospital utilisation. Patients included were those >65 years with emergency admission to acute provider in England (2012). RESULTS: Frailty syndrome models exhibited ROC scores of 0.624–0.659 for inpatient mortality, 0.63–0.654 for institutionalisation and 0.57–0.63 for 30-day emergency readmission. CONCLUSIONS: Frailty syndromes are a valid predictor of outcomes relevant to acute care. The models predictive power is in keeping with other scores in the literature, but is a simple, clinically relevant and potentially more acceptable measurement for use in the acute care setting. Predictive powers of the score are not sufficient for clinical use

Controlling alcohol availability through local policy: an observational study to evaluate Cumulative Impact Zones in a London borough

Background Cumulative impact zones (CIZs) are a discretionary policy lever available to local government, used to restrict the availability of alcohol in areas deemed already saturated. Despite little evidence of their effect, over 200 such zones have been introduced. This study explores the impact of three CIZs on the licensing of venues in the London Borough of Southwark. Methods Using 10 years of licensing data, we examined changes in the issuing of licences on the introduction of three CIZs within Southwark, relative to control areas. The number of licence applications made (N = 1110), the number issued, and the proportion objected to, were analysed using negative binomial regression. Results In one area tested, CIZ implementation was associated with 119% more licence applications than control areas (incidence rate ratios (IRR) = 2.19, 95% confidence intervals (CI): 1.29–3.73, P = 0.004) and 133% more licences granted (IRR = 2.33, 95% CI: 1.31–4.16, P = 0.004). No significant effect was found for the other two areas. CIZs were found to have no discernible effect on the relative proportion of licence applications receiving objections. Conclusions CIZs are proposed as a key lever to limit alcohol availability in areas of high outlet density. We found no evidence that CIZ establishment reduced the number of successful applications in Southwark