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The aim of the Health and Life Survey was to collect information about the health and lifestyles of the adult population of Edinburgh, in order to obtain accurate local baseline data against which Lothian NHS Board could judge progress towards reducing inequalities and improving health. The objectives of the survey were: To monitor progress towards national and local targets as outlined in the Scottish Performance Assessment Framework To produce information which is useful to NHS Edinburgh and partner agencies for the promotion and planning of health and health services To disseminate the collected information widely to professionals and the public To produce information that helps design effective interventions to tackle inequalities in health To measure current health and lifestyle behaviours To provide baseline information to enable identification and monitoring of trends in health and lifestyle behaviour To provide a baseline for comparison against other Health Boards throughout Scotland Indicators of health improvement and inequalities form the first two sections of the Scottish Performance Assessment Framework. However, these indicators are calculated for larger populations than are appropriate for the type of specific interventions to be undertaken. At the same time, many of these population indicators focus only on illness or adverse health events. Whilst these are important, they do not provide the fuller picture necessary to inform action for improvement. What was needed was an accurate baseline against which Lothian NHS Board could judge progress towards reducing inequalities and improving health. V Stewart, C Morris, P Mackie, P Donnelly, Lothian NHS Board, Deaconess House.
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Continual improvement: The process of enhancing an organization's environmental management system to achieve improvement in overall energy and environmental performance in line with the organization's environmental policy. This widely adopted principle is intended to ensure that an organization does not simply adopt an environmental management system for cosmetic purposes and thereby remain static, without commitment to reduce its impact on the environment. Emergency Response Plan: A formal, detailed plan that describes an organization's specific logistics and reporting requirements in the event of an emergency, such as fires, erosion or spills. A fundamental element of an environmental management system. Energy Efficiency: An increase in the energy efficiency is when either energy inputs are reduced for a given level of service, or there are increased or enhanced services for a given amount of energy inputs downloaded from eia.doe.gov emeu efficiency definition on 12 18 2003 ; . Also, a nomenclature given to products or systems that use less energy and have the same or better performance than conventional products or systems downloaded from tahoesolar Definitions on 12 18 2003 ; . Environment: Surroundings in which an organization or facility operates, including air, water, land, natural resources, flora, fauna, humans and their interrelation. Environmental Aspect: Element of an organization's activities, products or services that can interact with the environment definition from ISO 14001 ; . Environmental Impact: Any change to the environment, whether adverse or beneficial, wholly or partly arising from an organization's activities, products or services definition from ISO 14001 ; . Environmental Management Representative EMR ; : The clearly-identified environmental management system team leader who has responsibility for planning and facilitating an organization's environmental management system from start to finish and has the designated authority of senior manager to get the job done and ponstel, because birth control.
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Abstract 162 USING AN ONLINE SURVEY TO EVALUATE PATIENT SATISFACTION WITH ANTIHYPERTENSIVE MEDICATIONS Kristina Chen, PharnD, MS, Chiun-Fang Chiou, PhD, Research, Zynx Health Incorporated, Beverly Hills, CA, Craig A. Plauschinat, PharmD, Health Economics & Outcomes Research, Novartis Pharmaceuticals Corp., East Hanover, NJ, UK, Feride H. Frech, MPH, RPh, Health Economics & Outcomes Research, Novartis Pharmaceuticals Corp., East Hanover, NJ, Robert Dubois, MD, PhD, Anne Harper, PhD, Research, Zynx Health Incorporated, Beverly Hills, CA The Internet offers a new way of collecting patient-reported outcomes. Conducting surveys through mailing, phone, or in person is a less cost-effective process than using the Internet. The former methods of data collection require applying for institutional review board IRB ; approval, identifying the most adequate patient recruitment method and implementing the survey. We conducted a case study of adapting an online survey using a national patient panel to evaluate patient satisfaction with their antihypertensive medications. The survey was launched in September 2003 to gather rate of adverse effects, likelihood of continuing medication, drug switching behavior, and reasons for switching from a chronic disease panel. The survey was sent via email to almost 200, 000 members of the panel self-reporting hypertension. A screening survey was used to identify patients receiving either diuretics, angiotensin II receptor blockers, ACE inhibitors, calcium channel blockers or beta-blockers, and to exclude patients on multiple therapies as well as those receiving the antihypertensive medication for less than one month. To increase generalizability of our sample, data were adjusted with weights obtained from the NHANES database. Pairwise comparisons among different drug classes were conducted with Tukey adjustment. Since patients had previously consented to participate in the panel, the IRB process was handled and maintained by the company who owns the panel. A pilot test was conducted in a sample of the panel to identify and correct problems with the survey questions. This phase, including revisions to the survey, and fielding of the final survey took approximately three weeks. Surveys were completed by 1, 256 panel members 23% response rate ; with a mean age of 56.8 + - 14.2 years old, and 57.9% were female. The survey captured differences by drug class in all parameters measured. Online survey proved to be a cost-effective approach for collection patient-reported outcome data. Information obtained from this study may aid physicians in medication selection and ongoing monitoring for patients.
8. Yamaguchi, D. T., Hahn, T. J., Iida-Klein, A Kleeman, C. R., and Muallem, S. 1987 ; J. Biol. Chem. 2 6 2 , 7711-7718 9. Murphy, K. M. M., Gould, R. J., Largent, B. L., and Snyder, S. H. 1983 ; Proc. Natl. Acud. Sci. U. S. A. 80, 860-864 10. Rodan, S. B., Egan, J. J., Golub, E. E., and Rodan, G. A. 1980 ; Biochem. J. 186, 617-627 11. Reynolds, I. J., Snowman, A. M., and Snyder, S. H. 1986 ; J. Pharmacol. Exp. Ther. 237, 731-738 12. Wagner, J. A., Guggino, S. E., Reynolds, I. J., Snowman, A. M., Biswas, A., Olivera, B. M., and Snyder, S. H. 1988 ; Ann. N . Y. Acud. Sci. 622, 116177 and metaproterenol.
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Factors, together with age and gender, will give VALUE one of its unique features, the possibility of assessing the predictive power of an up-to-date cardiovascular risk scale in a large population of treated hypertensive patients traditionally considered to be at high risk of a cardiovascular event. The risk factors to be used in the VALUE trial include diabetes mellitus, cigarette smoking, hypercholesterolaemia, left ventricular hypertrophy without strain diagnosed on electrocardiogram, proteinuria, and serum creatinine above 1.7 mg dl. Disease factors include: documented history of myocardial infarction, peripheral vascular disease, stroke or transient ischaemic attack, or the presence of left ventricular hypertrophy with strain on ECG Table I ; . The age risk stratification runs as follows: --For male patients aged between 50 and 59 years, at least three 3 ; risk factors or one 1 ; disease factor is required to be entered into the trial. For female patients between 50 and 59 years, at least two 2 ; risk factors AND one 1 ; disease factor are required. This is due to the lower risk profile of women of perimenopausal age. --Above the age of 60, gender as a cardiovascular risk factor does not differ between men and women. Thus, for men and women between 60 and 69, at least two 2 ; risk factors or one 1 ; disease factor is required. Finally, for patients above the age of 70, the predictive value of age as a risk factor increases significantly, and thus only one 1 ; risk factor or one 1 ; disease factor is required to enter the trial. Main exclusion criteria are: renal artery stenosis; pregnancy; acute myocardial infarction, percutaneous transluminal coronary angioplasty PTCA ; or Coronary artery bypass CABG ; within the last 3 months; clinically relevant valvular disease; cerebrovascular accident in the last 3 months; severe hepatic disease; severe chronic renal failure; CHF requiring ACE inhibitor therapy; patients on monotherapy with beta-blockers for both coronary artery disease and hypertension Table II ; . The primary variable to be assessed at the end of the VALUE trial is the time to the first cardiac morbidity or mortality event. Cardiac mortality is defined as sudden cardiac death, fatal acute myocardial infarction, death during or post PTCA or CABG, death due to congestive heart failure, and evidence of recent acute myocardial infarction on autopsy. Cardiac morbidity is defined as new or chronic congestive heart failure requiring hospitalization, non-fatal acute myocardial infarction, emergency thrombolysis or any other interventional procedure performed in order to prevent a full-blown myocardial infarction. Secondary variables include all cause mortality, cardiac mortality defined as for the primary endpoint, cardiac morbidity defined as for the primary endpoint and metoclopramide.
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Electroencephalograhic EEG ; biofeedback, often referred to as neurofeedback, is an operant conditioning procedure whereby an individual modifies the amplitude, frequency or coherency of the neurophysiological dynamics of his her own brain Fox & Rudell, 1968; Rosenfeld et al., 1969; Rosenfeld & Fox, 1971; Rosenfeld, 1990 ; . The exact physiological foundations of this process are not well understood; however, the practical ability of humans and animals to directly modify their scalp recorded EEG through feedback is well established Fox & Rudell, 1968; Hetzler et al., 1977; Rosenfeld et al., 1969; Sterman, 1996 ; . An emerging and promising treatment approach is the use of quantitative EEG technology and EEG biofeedback training for the treatment of mild to moderate TBI. One of the earliest EEG biofeedback studies was by Ayers 1987 ; , who used alpha QEEG training in 250 cases of individuals with brain injury and demonstrated a return to pre-morbid functioning in a significant number of cases. Peniston et al. 1993 ; reported improved symptomology using EEG biofeedback in Vietnam veterans with combat related posttraumatic disorders. Trudeau et al. 1998 ; reported high discriminant accuracy of QEEG for the evaluation of combat veterans with a history of blast injury. More recently Hoffman et al. 1995 ; , in a biofeedback study of 14 individuals with TBI, reported that approximately 60% of individuals with mild TBI showed improvement in self-reported symptoms and or cognitive performance as measured by the MicroCog assessment test after 40 sessions of QEEG biofeedback. Hoffman et al. 1995 ; also found statistically significant normalization of the QEEG in those individuals that showed clinical improvement. Subsequent studies by Hoffman et al. 1996a; 1996b ; confirmed and extended these findings by showing significant improvement within 510 sessions. A similar finding of QEEG normalization following EEG biofeedback was reported by Tinius and Tinius 1996 ; . Ham and Packard 1996 ; evaluated EEG biofeedback in 40 indi.
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