Improving data quality in English healthcare: from case studies to an applied framework

This Thesis argues that the quality of data for professionals and information for patients may be limiting healthcare in England. Data are required for individual care, for monitoring services for populations and as part of broader research and development. Similarly, informed patient consent and real involvement in their own care depend on information. Failings in these areas can lead to a fragmented National Health Service which is slow to change. A Data Quality Framework (DQF) is therefore the main product of the Thesis. Prominent Themes which should be addressed have been identified through four representative Case Studies. From national data collection in Intensive Care to Visual Impairment Notification, the Studies span the range from quantity to quality of life and related healthcare services. Datasets in the Studies are found to be poorly researched; lacking support for collection and management; and unlinked to information for patients. Assistance from technology is under developed, while overall costs and benefits of both data collection and provision of patient information are poorly documented. These Prominent Themes are augmented by National Constraints derived from a review of healthcare policies and strategies for Information Management & Technology (IM&T). Demands for data and information are increasing and the delivery structures of care are changing through policy pledges. At the same time, healthcare is officially described as "largely based on manual systems". Problems with the introduction of technology are demonstrated by three IM&T strategies from 1998 to 2002. Culture and change management in the NHS have only recently been identified as major research issues. The necessary "information infrastructure" for data collection and information provision is still not in place at 2004. The full Data Quality Framework has separate components for assessing an existing or proposed system (Step 1. Appraisal Tool) and introducing managed change (Step 2. Implementation Programme). It draws in particular on recent central initiatives paralleling the Prominent Themes with adjustments for the National Constraints. The central initiatives cover: evolving mechanisms for appraising and approving all national healthcare datasets; care process modelling to highlight sources of data and points for information provision to patients; principles for accrediting information providers, paralleling those for organisations involved in NHS research; and standards for labelling information resources for indexing and easier retrieval (meta-data) as part of the eGovemment Interoperability Framework for the whole public sector. Benefits are assessed by applying the DQF to the Visual Impairment Notification process and comparing a review of the same process by the Department of Health (still ongoing at late 2003). Application of the DQF produces formal evidence to justify and direct change. Recommendations include a new visual impairment identification form linked to information sources and monitoring mechanisms, with pilots in both electronic and paper formats. In contrast, interim proposals from the official review has provided only anecdotal evidence and three new forms without a clear logic to support content or completion practices. The official approach contradicts the Department of Health's own policies on broad consultation and standards for developing national datasets. Moreover, alternative approaches derived from the DQF cannot be developed without prior Department of Health approval. The DQF has not been fully applied and needs for refinement are acknowledged. Nevertheless, it is possibly the only example of its kind in English healthcare with general principles supported by evidence from the real world Case Studies

Reliability analysis of a timber truss system subjected to decay

Assessing the safety of existing timber structures is of paramount importance for taking reliable decisions on repair actions and their extent. The results obtained through semi-probabilistic methods are unrealistic, as the partial safety factors present in codes are calibrated considering the uncertainty exhibited by new structures. In order to overcome these limitations, and also to include the e ects of decay in the safety analysis, probabilistic methods, based on Monte-Carlo simulation are applied here to assess the safety of existing timber structures. In particular, the impact of decay on structural safety is analyzed and discussed using a simple structural model, similar to that used for current semi-probabilistic analysis.Fundação para a Ciência e a Tecnologia (FCT

Escape from Vela X

While the Vela pulsar and its associated nebula are often considered as the archetype of a system powered by a {approx} 10{sup 4} year old isolated neutron star, many features of the spectral energy distribution of this pulsar wind nebula are both puzzling and unusual. Here we develop a model that for the first time relates the main structures in the system, the extended radio nebula (ERN) and the X-ray cocoon through continuous injection of particles with a fixed spectral shape. We argue that diffusive escape of particles from the ERN can explain the steep Fermi-LAT spectrum. In this scenario Vela X should produce a distinct feature in the locally-measured cosmic ray electron spectrum at very high energies. This prediction can be tested in the future using the Cherenkov Telescope Array (CTA). If particles are indeed released early in the evolution of PWNe and can avoid severe adiabatic losses, PWN provide a natural explanation for the rising positron fraction in the local CR spectrum

Can social media reduce discrimination and ignorance towards patients with long term conditions? A chronic kidney disease example in the UK and more widely

Long Term Conditions (LTCs) are increasing in prevalence and cost in Western healthcare. Patients with such conditions are often classed as “disabled”, because of impacts of self-care on “activities of daily life” or secondary consequences of conditions (impairments) affecting factors such as mobility, concentration and communications. Disability needs are often ignored in the design of services and treatment of individuals. It manifests as services which some find difficult to use and lack of personal respect (discrimination) often based on lack of understanding by the healthcare profession itself (ignorance). This paper explores how Social Media (SM), an example “Assistive Technology” in an increasingly digital age, might help. The focus is Chronic Kidney Disease with two, specific illustrations in the UK beginning to spread worldwide. Support mechanisms now emerging may go well beyond healthcare, and even beyond kidney problems. They may also find additional assistance via the new, English Accessible Information Standard.This article is freely available via Open Access. Click on the 'Additional Link' above to access the full-text via the publisher's site.Published (Open Access

Mood instability, mental illness and suicidal ideas : results from a household survey

Purpose: There is weak and inconsistent evidence that mood instability (MI) is associated with depression, post traumatic stress disorder (PTSD) and suicidality although the basis of this is unclear. Our objectives were first to test whether there is an association between depression and PTSD, and MI and secondly whether MI exerts an independent effect on suicidal thinking over and above that explained by common mental disorders. Methods: We used data from the Adult Psychiatric Morbidity Survey 2007 (N = 7,131). Chi-square tests were used to examine associations between depression and PTSD, and MI, followed by regression modelling to examine associations between MI and depression, and with PTSD. Multiple logistic regression analyses were used to assess the independent effect of MI on suicidal thinking, after adjustment for demographic factors and the effects of common mental disorder diagnoses. Results: There are high rates of MI in depression and PTSD and the presence of MI increases the odds of depression by 10.66 [95 % confidence interval (CI) 7.51–15.13] and PTSD by 8.69 (95 % CI 5.90–12.79), respectively, after adjusting for other factors. Mood instability independently explained suicidal thinking, multiplying the odds by nearly five (odds ratio 4.82; 95 % CI 3.39–6.85), and was individually by some way the most important single factor in explaining suicidal thoughts. Conclusions: MI is strongly associated with depression and PTSD. In people with common mental disorders MI is clinically significant as it acts as an additional factor exacerbating the risk of suicidal thinking. It is important to enquire about MI as part of clinical assessment and treatment studies are required

BUMC Annual Report

Annual report of the Boston University Medical Center