Healthcare services managers: what information do they need and use?

Objectives: To gain insight into the information behaviour of healthcare services managers as they draw on information while engaged in decision making unrelated to individual patient care. Objectives – The purpose of this research project was to gain insight into the information behaviour of healthcare services managers as they use information while engaged in decision-making unrelated to individual patient care. Methods – This small-scale, exploratory, multiple case study used the critical incident technique in nineteen semi-structured interviews. Responses were analyzed using ‘Framework,’ a matrix-based content analysis system. Results – This paper presents findings related to the internal information that healthcare services managers need and use. Their decisions are influenced by a wide variety of factors. They must often make decisions without all of the information they would prefer to have. Internal information and practical experience set the context for new research-based information, so they are generally considered first. Conclusions – Healthcare services managers support decisions with both facts and value-based information. These results may inform both delivery of health library services delivery and strategic health information management planning. They may also support librarians who extend their skills beyond managing library collections and teaching published information retrieval skills, to managing internal and external information, teaching information literacy, and supporting information sharing

A Power-Enhanced Algorithm for Spatial Anomaly Detection in Binary Labelled Point Data Using the Spatial Scan Statistic [postprint]

This paper presents a novel modification to an existing algorithm for spatial anomaly detection in binary labeled point data sets, using the Bernoulli version of the Spatial Scan Statistic. We identify a potential ambiguity in p-values produced by Monte Carlo testing, which (by the selection of the most conservative p-value) can lead to sub-optimal power. When such ambiguity occurs, the modification uses a very inexpensive secondary test to suggest a less conservative p-value. Using benchmark tests, we show that this appears to restore power to the expected level, whilst having similarly retest variance to the original. The modification also appears to produce a small but significant improvement in overall detection performance when multiple anomalies are present

Information sheets for patients with acute chest pain: randomised controlled trial

Objectives: To determine whether providing an information sheet to patients with acute chest pain reduces anxiety, improves health related quality of life, improves satisfaction with care, or alters subsequent symptoms or actions. Design: Single centre, non-blinded, randomised controlled trial. Setting: Chest pain unit of an emergency department. Participants: 700 consecutive patients with acute chest pain and no clear diagnosis at initial presentation. Interventions: After a diagnostic assessment patients were randomised to receive either standard verbal advice or verbal advice followed by an information sheet. Main outcome measures: The primary outcome was anxiety (hospital anxiety and depression scale). Secondary outcomes were depression (hospital anxiety and depression scale), health related quality of life (SF-36), patient satisfaction, presentation with further chest pain within one month, lifestyle change (smoking cessation, diet, exercise), further information sought from other sources, and planned healthcare seeeking behaviour in response to further pain. Results 494 of 700 (70.6%) patients responded. Compared with those receiving standard verbal advice those receiving advice and an information sheet had lower mean hospital anxiety and depression scale scores for anxiety (7.61v8.63, difference 1.02, 95% confidence interval 0.20 to 1.84) and depression (4.14 v 5.28, difference 1.14, 0.41 to 1.86) and higher scores for mental health and perception of general health on the SF-36. The information sheet had no significant effect on satisfaction with care, subsequent symptoms, lifestyle change, information seeking, or planned actions in the event of further pain. Conclusions: Provision of an information sheet to patients with acute chest pain can reduce anxiety and depression and improve mental health and perception of general health but does not alter satisfaction with care or other outcomes. Trial registration Current Controlled Trials ISRCTN85248020

Predicting loneliness in older age using two measures of loneliness

Older people are especially vulnerable to loneliness and this has become a major public health concern for people in later life. In this paper, we propose a machine learning based approach to predict loneliness probability using two gradient boosting algorithms, XGBoost and LightGBM. The predictive models are built using data from a large nationally representative sample from, the English Longitudinal Study of Ageing (ELSA) that had seven successive waves (2002–2015). Two measures of loneliness were applied to investigate the impact of different measure strategies on the prediction of loneliness. The models achieved good performance with a high Area Under Curve (AUC) and a low Logarithmic Loss (LogLoss) on the test data, i.e. AUC (0.88) and LogLoss (0.24) using the single-item direct measure of loneliness, and AUC (0.84) and LogLoss (0.31) using the multi-item indirect measure of loneliness. A wide range of variables were investigated to identify significant risk factors associated with loneliness. Specific categories associated with important variables were also recognized by the models. Such information will further enhance our understanding and knowledge of the causes of loneliness in elderly people

The use of data mining methods for the prediction of dementia : evidence from the English longitudinal study of aging

Dementia in older age is a major health concern with the increase in the aging population. Preventive measures to prevent or delay dementia symptoms are of utmost importance. In this study, a large and wide variety of factors from multiple domains were investigated using a large nationally-representative sample of older people from the English Longitudinal Study of Ageing (ELSA). Seven machine learning algorithms were implemented to build predictive models for performance comparison. A simple model ensemble approach was used to combine the prediction results of individual base models to further improve predictive power. A series of important factors in each domain area were identified. The findings from this study provide new evidence on factors that are associated with the dementia in later life. This information will help our understanding of potential risk factors for dementia and identify warning signs of the early stages of dementia. Longitudinal research is required to establish which factors may be causative and which factors may be a consequence of dementia

A graph-theory method for pattern identification in geographical epidemiology - a preliminary application to deprivation and mortality

Background: Graph theoretical methods are extensively used in the field of computational chemistry to search datasets of compounds to see if they contain particular molecular substructures or patterns. We describe a preliminary application of a graph theoretical method, developed in computational chemistry, to geographical epidemiology in relation to testing a prior hypothesis. We tested the methodology on the hypothesis that if a socioeconomically deprived neighbourhood is situated in a wider deprived area, then that neighbourhood would experience greater adverse effects on mortality compared with a similarly deprived neighbourhood which is situated in a wider area with generally less deprivation. Methods: We used the Trent Region Health Authority area for this study, which contained 10,665 census enumeration districts (CED). Graphs are mathematical representations of objects and their relationships and within the context of this study, nodes represented CEDs and edges were determined by whether or not CEDs were neighbours (shared a common boundary). The overall area in this study was represented by one large graph comprising all CEDs in the region, along with their adjacency information. We used mortality data from 1988-1998, CED level population estimates and the Townsend Material Deprivation Index as an indicator of neighbourhood level deprivation. We defined deprived CEDs as those in the top 20% most deprived in the Region. We then set out to classify these deprived CEDs into seven groups defined by increasing deprivation levels in the neighbouring CEDs. 506 (24.2%) of the deprived CEDs had five adjacent CEDs and we limited pattern development and searching to these CEDs. We developed seven query patterns and used the RASCAL (Rapid Similarity Calculator) program to carry out the search for each of the query patterns. This program used a maximum common subgraph isomorphism method which was modified to handle geographical data. Results: Of the 506 deprived CEDs, 10 were not identified as belonging to any of the seven groups because they were adjacent to a CED with a missing deprivation category quintile, and none fell within query Group 1 (a deprived CED for which all five adjacent CEDs were affluent). Only four CEDs fell within Group 2, which was defined as having four affluent adjacent CEDs and one non-affluent adjacent CED. The numbers of CEDs in Groups 3-7 were 17, 214, 95, 81 and 85 respectively. Age and sex adjusted mortality rate ratios showed a non-significant trend towards increasing mortality risk across Groups (Chi-square = 3.26, df = 1, p = 0.07). Conclusion: Graph theoretical methods developed in computational chemistry may be a useful addition to the current GIS based methods available for geographical epidemiology but further developmental work is required. An important requirement will be the development of methods for specifying multiple complex search patterns. Further work is also required to examine the utility of using distance, as opposed to adjacency, to describe edges in graphs, and to examine methods for pattern specification when the nodes have multiple attributes attached to them

The ‘total cost of publication’ in a hybrid open-access environment: Institutional approaches to funding journal article-processing charges in combination with subscriptions

As open-access (OA) publishing funded by article-processing charges (APCs) becomes more widely accepted, academic institutions need to be aware of the ‘total cost of publication’, comprising subscription costs plus APCs and additional administration costs. This study analyses data from 23 UK institutions covering the period 2007 to 2014 modelling the total cost of publication (TCP). It shows a clear rise in centrally-managed APC payments from 2012 onwards, with payments projected to increase further. As well as evidencing the growing availability and acceptance of OA publishing, these trends reflect particular UK policy developments and funding arrangements intended to accelerate the move towards OA publishing (‘Gold’ OA). Whilst the mean value of APCs has been relatively stable, there was considerable variation in APC prices paid by institutions since 2007. In particular, ‘hybrid’ subscription/OA journals were consistently more expensive than fully-OA journals. Most APCs were paid to large ‘traditional’ commercial publishers who also received considerable subscription income. New administrative costs reported by institutions varied considerably. The total cost of publication modelling shows that APCs are now a significant part of the TCP for academic institutions, in 2013 already constituting an average of 10% of the TCP (excluding administrative costs)