A study of nutrition promotion in and consumer nutrition environments of hospitals

Dietary intake is a complex, health-related behavior, and although individual-level theoretical models explain some variation in dietary intake, comprehensive theoretical models such as the ecological framework describe the multiple levels which influence diet-related behaviors. Thus, the ecological framework is a preferred model for designing comprehensive nutrition interventions. While ecological-based nutrition interventions have been described, little work has focused on interventions in the hospital setting. Because hospitals are considered the hallmarks of health, it might seem that hospitals would regularly engage in worksite nutrition promotion; however, recent publications and other anecdotal evidence have indicated otherwise. The first paper of this dissertation systematically reviewed the scientific literature between 1996 and 2012 and identified 13 outcome evaluation trials for hospital-based worksite nutrition interventions. Of these 13 interventions, only one intervention targeted three of the four levels of the ecological framework and no intervention targeted all four levels. Only half of the interventions targeted the physical environment of hospitals, thus warranting more investigation into this specific level of the ecological framework in this setting. ^ A critical type of nutrition-related physical environments is the consumer nutrition environment. Although other tools measure the consumer nutrition environments of stores and restaurants, no tool specifically measured the consumer nutrition environments of hospitals until the CDC developed the Healthy Hospital Environment Scan for Cafeterias, Vending Machines, and Gift Shops (HHES-CVG). The HHES-CVG, a tool which measures the consumer nutrition environments of hospital cafeterias, vending machines, and gifts shops, was released in November 2011, and in the second paper of this dissertation, the reliability of this tool was investigated. Two trained raters visited 39 hospitals across Southern California between February and May 2012, and based on analyses of the raters' findings, the HHES-CVG exhibited strong reliability metrics (inter-observer agreement between 74 and 100%, and an intraclass correlation coefficient of 0.961 for the overall nutrition composite score). Because the HHES-CVG was found to be a reliable tool, the third paper of this dissertation presented HHES-CVG results from the 39 hospitals. Overall, hospitals only scored about one-fourth of the total possible points for the nutrition composite score, indicating that most facilities do not have acceptable consumer nutrition environments. Some of the best practices observed in cafeterias were significantly associated with having a large facility and with having a contracted foodservice operation, but overall nutrition composite score was not associated with any specific facility or operation type. ^ The dissertation concluded that much work is needed in order to improve the consumer nutrition environments of hospitals. Practitioners and healthcare administrators should consider starting with ecological-based interventions addressing all levels including the physical environment.^

Efficiency from pharmacy inventory technology: A means to improving quality in non-profit hospitals

Hospitals, like all organizations, have both a mission and a finite supply of resources with which to accomplish that mission. Because the inventory of therapeutic drugs is among the more expensive resources needed by a hospital to achieve its mission, a conceptual model of structure plus process equals outcome posits that adequate emphasis should be placed on optimization of the organization's investment in this important structural resource to provide highest quality outcomes. Therefore emphasis should be placed on the optimization of pharmacy inventory because lowering the financial investment in drug inventory and associated costs increases productive efficiency, a key element of quality. ^ In this study, a post-intervention analysis of a hospital pharmacy inventory management technology implementation at The University of Texas M.D. Anderson Cancer Center was conducted to determine if an intervention which reduced a hospital's financial investment in pharmaceutical inventory provided an opportunity to incrementally optimize the organization's mix of structural resources thereby improving quality of care. The results suggest that hospital pharmacies currently lacking technology to support automated purchasing logistics and perpetual, real-time inventory management for drugs may achieve measurable benefits from the careful implementation of such technology, enabling the hospital to lower its investment in on-hand inventory and, potentially, to reduce overall purchasing expenditures. ^ The importance of these savings to the hospital and potentially to the patient should not be underestimated for their ability to generate funding for previously unfunded public health programs or in their ability to provide financial relief to patients in the form of lower drug costs given the current climate of escalating healthcare costs and tightening reimbursements.^

Comparing the quality of three models of postabortion care in public hospitals in Mexico City

artículo publicado en la revista Int Fam Plan Perspect. 2003 Sep;29(3):112-20

Communication Architecture for Tracking and Interoperable Services at Hospitals: A Real Deployment Experience

Any new hospital communication architecture has to support existing services, but at the same time new added features should not affect normal tasks. This article deals with issues regarding old and new systems’ interoperability, as well as the effect the human factor has in a deployed architecture. It also presents valuable information, which is a product of a real scenario. Tracking services are also tested in order to monitor and administer several medical resources.

Service Capacity Reserve under Uncertainty by Hospital’s ER Analogies: A Practical Model for Car Services

We define a capacity reserve model to dimension passenger car service installations according to the demographic distribution of the area to be serviced by using hospital?s emergency room analogies. Usually, service facilities are designed applying empirical methods, but customers arrive under uncertain conditions not included in the original estimations, and there is a gap between customer?s real demand and the service?s capacity. Our research establishes a valid methodology and covers the absence of recent researches and the lack of statistical techniques implementation, integrating demand uncertainty in a unique model built in stages by implementing ARIMA forecasting, queuing theory, and Monte Carlo simulation to optimize the service capacity and occupancy, minimizing the implicit cost of the capacity that must be reserved to service unexpected customers. Our model has proved to be a useful tool for optimal decision making under uncertainty integrating the prediction of the cost implicit in the reserve capacity to serve unexpected demand and defining a set of new process indicators, such us capacity, occupancy, and cost of capacity reserve never studied before. The new indicators are intended to optimize the service operation. This set of new indicators could be implemented in the information systems used in the passenger car services.

KDIGO-based acute kidney injury criteria operate differently in hospitals and the community—findings from a large population cohort

ACKNOWLEDGEMENTS We acknowledge the data management support of Grampian Data Safe Haven (DaSH) and the associated financial support of NHS Research Scotland, through NHS Grampian investment in the Grampian DaSH. S.S. is supported by a Clinical Research Training Fellowship from the Wellcome Trust (Ref 102729/Z/13/Z). We also acknowledge the support from The Farr Institute of Health Informatics Research. The Farr Institute is supported by a 10-funder consortium: Arthritis Research UK, the British Heart Foundation, Cancer Research UK, the Economic and Social Research Council, the Engineering and Physical Sciences Research Council, the Medical Research Council, the National Institute of Health Research, the National Institute for Social Care and Health Research (Welsh Assembly Government), the Chief Scientist Office (Scottish Government Health Directorates) and the Wellcome Trust (MRC Grant Nos: Scotland MR/K007017/1).

The epidemiology of antibiotic resistance in hospitals: Paradoxes and prescriptions

A simple mathematical model of bacterial transmission within a hospital was used to study the effects of measures to control nosocomial transmission of bacteria and reduce antimicrobial resistance in nosocomial pathogens. The model predicts that: (i) Use of an antibiotic for which resistance is not yet present in a hospital will be positively associated at the individual level (odds ratio) with carriage of bacteria resistant to other antibiotics, but negatively associated at the population level (prevalence). Thus inferences from individual risk factors can yield misleading conclusions about the effect of antibiotic use on resistance to another antibiotic. (ii) Nonspecific interventions that reduce transmission of all bacteria within a hospital will disproportionately reduce the prevalence of colonization with resistant bacteria. (iii) Changes in the prevalence of resistance after a successful intervention will occur on a time scale of weeks to months, considerably faster than in community-acquired infections. Moreover, resistance can decline rapidly in a hospital even if it does not carry a fitness cost. The predictions of the model are compared with those of other models and published data. The implications for resistance control and study design are discussed, along with the limitations and assumptions of the model.