The UK NHS Economic Evaluation Database : Economic issues in evaluations of health technology

Objective: The U.K. NHS Economic Evaluation Database (EED) project is commissioned to identify papers on economic evaluations of health technologies and to disseminate their findings to NHS decision makers by means of structured abstracts that are available through a public database and the Cochrane Library. This paper discusses current issues relating to the economic aspects of producing NHS EED abstracts. Methods: A review of NHS EED was undertaken between 1994 and 1999 to determine the methodologies adopted and issues that influence the usefulness of economic evaluations. Methods adopted to improve the quality of NHS EED abstracts are also reported. Results: Eighty-five percent of NHS EED abstracts are cost-effectiveness analyses (CEAs), 9.3% are cost-utility analyses (CUAs), and only 1.4% are cost-benefit analyses (CBAs). Of the total abstracts, 65.9% are based on single studies, 19.5% on reviews, 3.9% on estimates of effectiveness, and 10.7% on combinations of these sources. Models are utilized in 16.7% of CEAs, 60.2% of CUAs, and 20% of CBAs. Analyses of CBA studies reveal a degree of misuse of well-established definitions. NHS EED internal control mechanisms are reported that provide a means of ensuring that abstracts are based on sound academic principles. Conclusions: Most economic evaluations are conducted by means of CEA, followed by CUA, while CBA accounts for an extreme minority of cases. Single studies form the principal source of effectiveness data, although models are widely used, principally in CUA. The structure of NHS EED abstracts provides decision makers with the principal results and an interpretation of the relative strengths and weaknesses of economic evaluations

The spatial ecology of free-ranging domestic pigs (Sus scrofa) in western Kenya

Background In many parts of the developing world, pigs are kept under low-input systems where they roam freely to scavenge food. These systems allow poor farmers the opportunity to enter into livestock keeping without large capital investments. This, combined with a growing demand for pork, especially in urban areas, has led to an increase in the number of small-holder farmers keeping free range pigs as a commercial enterprise. Despite the benefits which pig production can bring to a household, keeping pigs under a free range system increases the risk of the pig acquiring diseases, either production-limiting or zoonotic in nature. This study used Global Positioning System (GPS) technology to track free range domestic pigs in rural western Kenya, in order to understand their movement patterns and interactions with elements of the peri-domestic environment. Results We found that these pigs travel an average of 4,340 m in a 12 hr period and had a mean home range of 10,343 m2 (range 2,937–32,759 m2) within which the core utilisation distribution was found to be 964 m2 (range 246–3,289 m2) with pigs spending on average 47% of their time outside their homestead of origin. Conclusion These are the first data available on the home range of domestic pigs kept under a free range system: the data show that pigs in these systems spend much of their time scavenging outside their homesteads, suggesting that these pigs may be exposed to infectious agents over a wide area. Control policies for diseases such as Taenia solium, Trypanosomiasis, Trichinellosis, Toxoplasmosis or African Swine Fever therefore require a community-wide focus and pig farmers require education on the inherent risks of keeping pigs under a free range system. The work presented here will enable future research to incorporate movement data into studies of disease transmission, for example for the understanding of transmission of African Swine Fever between individuals, or in relation to the life-cycle of parasites including Taenia solium

Shrinking a large dataset to identify variables associated with increased risk of Plasmodium falciparum infection in Western Kenya

Large datasets are often not amenable to analysis using traditional single-step approaches. Here, our general objective was to apply imputation techniques, principal component analysis (PCA), elastic net and generalized linear models to a large dataset in a systematic approach to extract the most meaningful predictors for a health outcome. We extracted predictors for Plasmodium falciparum infection, from a large covariate dataset while facing limited numbers of observations, using data from the People, Animals, and their Zoonoses (PAZ) project to demonstrate these techniques: data collected from 415 homesteads in western Kenya, contained over 1500 variables that describe the health, environment, and social factors of the humans, livestock, and the homesteads in which they reside. The wide, sparse dataset was simplified to 42 predictors of P. falciparum malaria infection and wealth rankings were produced for all homesteads. The 42 predictors make biological sense and are supported by previous studies. This systematic data-mining approach we used would make many large datasets more manageable and informative for decision-making processes and health policy prioritization

Outcomes of service encounter quality in a business-to-business context

Service encounter quality is an area of growing interest to researchers and managers alike, yet little is known about the effects of face-to-face service encounter quality within a business-to-business setting. In this paper, a psychometrically sound measure of such service encounter quality is proposed, and consequences of this construct are empirically assessed. Both a literature review and a dyadic in-depth interview approach were used to develop a conceptual framework and a pool of items to capture service encounter quality. A mail survey of customers was undertaken, and a response rate of 36% was obtained. Data analysis was conducted via confirmatory factor analysis and structural equation modeling. Findings reveal a four-factor structure of service encounter quality, encompassing professionalism, civility, friendliness and competence dimensions. Service encounter quality was found to be directly related to customer satisfaction and service quality perceptions, and indirectly to loyalty. The importance of these findings for practitioners and for future research on service encounter quality is discussed

The genetic case for cardiorespiratory fitness as a clinical vital sign and the routine prescription of physical activity in healthcare

Background: Cardiorespiratory fitness (CRF) and physical activity (PA) are well-established predictors of morbidity and all-cause mortality. However, CRF is not routinely measured and PA not routinely prescribed as part of standard healthcare. The American Heart Association (AHA) recently presented a scientific case for the inclusion of CRF as a clinical vital sign based on epidemiological and clinical observation. Here, we leverage genetic data in the UK Biobank (UKB) to strengthen the case for CRF as a vital sign and make a case for the prescription of PA. / Methods: We derived two CRF measures from the heart rate data collected during a submaximal cycle ramp test: CRF-vo2max, an estimate of the participants' maximum volume of oxygen uptake, per kilogram of body weight, per minute; and CRF-slope, an estimate of the rate of increase of heart rate during exercise. Average PA over a 7-day period was derived from a wrist-worn activity tracker. After quality control, 70,783 participants had data on the two derived CRF measures, and 89,683 had PA data. We performed genome-wide association study (GWAS) analyses by sex, and post-GWAS techniques to understand genetic architecture of the traits and prioritise functional genes for follow-up. / Results: We found strong evidence that genetic variants associated with CRF and PA influenced genetic expression in a relatively small set of genes in the heart, artery, lung, skeletal muscle and adipose tissue. These functionally relevant genes were enriched among genes known to be associated with coronary artery disease (CAD), type 2 diabetes (T2D) and Alzheimer’s disease (three of the top 10 causes of death in high-income countries) as well as Parkinson’s disease, pulmonary fibrosis, and blood pressure, heart rate, and respiratory phenotypes. Genetic variation associated with lower CRF and PA was also correlated with several disease risk factors (including greater body mass index, body fat and multiple obesity phenotypes); a typical T2D profile (including higher insulin resistance, higher fasting glucose, impaired beta-cell function, hyperglycaemia, hypertriglyceridemia); increased risk for CAD and T2D; and a shorter lifespan. / Conclusions: Genetics supports three decades of evidence for the inclusion of CRF as a clinical vital sign. Given the genetic, clinical and epidemiological evidence linking CRF and PA to increased morbidity and mortality, regular measurement of CRF as a marker of health and routine prescription of PA could be a prudent strategy to support public health