Underuse of indicated medications in elderly

Introduction: Treatment omissions are very important to value the quality of pharmacological therapy. In fact, suboptimal prescribing has been defined as overuse (polypharmacy), inappropriate prescribing (drug whose risks are greater than the benefits in older adults) and underuse of indicated medications. This omission of drug therapy may be linked to certain health outcomes in older patients, such as, for instance, the greater risk of cardiovascular events and mortality Material and methods: A cross-sectional study was performed. The study population comprised 407 community-dwelling residents over the age of 65 on Lanzarote (Canary Islands, Spain), where there are 15 primary healthcare centres. Data recorded included socio-demographic characteristics, clinical status, functional and cognitive assessment, and complete information about drugs intake. Potential prescribing omissions (PPO) were evaluated according to Screening Tool to Alert doctors to Right Treatment (START). Results: A total of 1844 medications were prescribed to the patients included in our study (median number per patient: 4.5 drugs; range: 0-14: polypharmacy prevalence: 45%). Omeprazole was the most frequently used drug followed by aspirin, furosemide and enalapril. START identified PPO in 170 (41.8%) subjects. Sixteen of the 22 START criteria (72.7%) were used to identify these PPO. The endocrine system accounted for over half the omissions (51.8%), followed by the cardiovascular system (26.7%), where the main omission was anticoagulants in the presence of chronic atrial fibrillation. Multiple logistic regression analysis revealed that the risk of PPO increased by 60% for every additional point in the Charlson Comorbidity Index (OR 1.60, 95% CI 1.35-1.91). Increasing numbers of medications also independently predicted the odds of at least one PPO according to START criteria (OR 2.19, 95% CI 1.36-3.55). Conclusions: Our findings show high rates of polypharmacy and PPO, as well as a clear relationship between these two concepts.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tec

Potential prescribing omissions vs polypharmacy among elderly patients

Objective: Screening tools have been formulated to identify potentially inappropriate prescribing (PIP) in older people. Screening Tool of Older Person’s Prescriptions (STOPP) and Screening Tool to Alert doctors to Right Treatment (START) have been developed to identify PIP and potential prescribing omissions (PPOs). Although there are many publications on PIP, very few studies have analyzed the omissions. The aim was to measure the prevalence rates of potential PPOs using START. Methods: A cross-sectional study was undertaken on a total of 407 patients aged 65 years or older, who accepted face-to-face questionnaires. Study setting: 15 public primary care centers in Lanzarote (Spain). Data recorded included socio-demographic characteristics, clinical status, functional and cognitive assessment, and complete information about drugs intake. Polypharmacy was defined as treatment with five or more medications. POPs were evaluated according to START criteria. Results: Mean age was 79.3; 57.2% were females. The average CCI was 1.95 and 34.6% of the patients had CCI scores >2. Total number of medicines prescribed was 1831 (median 4.5±2.9). 183 (45%) of outpatients were polimedicated. The most widely prescribed ATC groups were C (69.5% of the patients had at least one drug from this group), A (53.6%) and N (51.6%). A total of 303 PPOs were identified in 41.85% (170) of patients. The most common were metmorfin with Type 2 diabetes (DM) ± metabolic syndrome (24%), statin therapy in DM if coexisting major cardiovascular risk factors present (13%) and antiplatelet therapy in DM with co-existing major cardiovascular risk factors (7.5%). The risk of PPOs increased with an increasing number of drugs (OR 1.21, 95% CI 1.12-1.32) and with the presence of cardiovascular disease (OR 1.67, 95% CI 1.01-2.87). Conclusion: Although polypharmacy rates are high, we detected a significant percentage of potentially beneficial treatment omissions, mainly in endocrine and cardiovascular systems.Universidad de Málaga. Campus de Excelencia Internacional andalucia Tec

Multilevel Zero-One Inflated Beta Regression Model for the Analysis of the Relationship between Exogenous Health Variables and Technical Efficiency in the Spanish National Health System Hospitals

Background: This article proposes a methodological innovation in health economics for the second stage analysis of technical efficiency in hospitals. It investigates the relationship between the installed capacity in regions and hospitals and their ownership structure. Methods: A multilevel zero-one inflated beta regression model is employed to model pure technical efficiency more adequately than other models frequently used in econometrics. Results: Compared to publicly managed hospitals, the mean efficiency index of hospitals with public-private partnership (PPP) formulas was 4.27-fold. This figure was 1.90-fold for private hospitals. Concerning the efficiency frontier, the odds ratio (OR) of PPP models vs. public hospitals was 42.06. The OR of private hospitals vs. public hospitals was 8.17. A one standard deviation increase in the percentage of beds in intensive care units increases the odds of being situated on the efficiency frontier by 50%. Conclusions: The proportion of hospital beds in intensive care units relates to a higher chance of being on the efficiency frontier. Hospital ownership structure is related to the mean efficiency index of Spanish National Health Service hospitals, as well as the odds of being situated on the efficiency frontier.EUROPEAN REGIONAL DEVELOPMENT FUND (Operative Program: Andalusia 2014–2020. Ministry of Economy. Knowledge. Business and University. Junta de Andalucía. Spain. Grant number: B-SEJ-266-UGR18

Space.time interpolation of daily air temperatures

We propose a model to describe the mean function as well as the spatio-temporal covariance structure of 15 years of both maximum and minimum daily temperature data from 190 stations throughout the region of Catalonia (Spain), with daily data covering the period 1994-2008. Our aim is threefold: (a) estimation of the long-term trend of maximum and minimum temperatures; (b) assessing the spatial and temporal variability of temperatures, and (c) interpolation of the spatial temperatures at any given time. Long-term trend, annual harmonics and winds were considered as explanatory vari- ables of the mean function. The parameters associated with these variables were allowed to vary between stations and within each year. We controlled temporal autocorrelation by means of ARMA models. For the spatial covariance structure we used the Mat ern family of covariance functions and a nugget term. Spatio-temporal models were built as Bayesian hierarchical models with two stages following the integrated nested place Laplace approximation (INLA) for Bayesian inference. For the nal model estimation we used a two-stage approach, in which we rst assumed the stations were spatially independent, and then we modeled the spatio-temporal covariance using the interim posterior from the residuals of the model in the rst-stage as prior distributions of replications of a spatial process. We allowed all spatial parameters to also vary with time

Spatio-temporal trends of mortality in small areas of Southern Spain

Background: Most mortality atlases show static maps from count data aggregated over time. This procedure has several methodological problems and serious limitations for decision making in Public Health. The evaluation of health outcomes, including mortality, should be approached from a dynamic time perspective that is specific for each gender and age group. At the moment, researches in Spain do not provide a dynamic image of the population’s mortality status from a spatio-temporal point of view. The aim of this paper is to describe the spatial distribution of mortality from all causes in small areas of Andalusia (Southern Spain) and evolution over time from 1981 to 2006. Methods: A small-area ecological study was devised using the municipality as the unit for analysis. Two spatiotemporal hierarchical Bayesian models were estimated for each age group and gender. One of these was used to estimate the specific mortality rate, together with its time trends, and the other to estimate the specific rate ratio for each municipality compared with Spain as a whole. Results: More than 97% of the municipalities showed a diminishing or flat mortality trend in all gender and age groups. In 2006, over 95% of municipalities showed male and female mortality specific rates similar or significantly lower than Spanish rates for all age groups below 65. Systematically, municipalities in Western Andalusia showed significant male and female mortality excess from 1981 to 2006 only in age groups over 65. Conclusions: The study shows a dynamic geographical distribution of mortality, with a different pattern for each year, gender and age group. This information will contribute towards a reflection on the past, present and future of mortality in Andalusia.Ye

Guía de indicadores para medir las desigualdades de género en salud y sus determinantes

Los indicadores de género son de utilidad para señalar cambios en el estatus y rol de las mujeres y de los hombres en distintos momentos del tiempo, y por tanto, ofrecer una imagen dinámica de la situación de la equidad de género en un contexto social determinado. La Ley Orgánica 3/2007, de 22 de marzo, para la igualdad efectiva de mujeres y hombres, en su artículo 20, insta a los poderes públicos a que incluyan en sus estudios y estadísticas, nuevos indicadores que posibiliten un mejor conocimiento de las diferencias en los valores, roles, situaciones, condiciones, aspiraciones y necesidades de mujeres y hombres. En el contexto andaluz, la Ley de Salud Pública de Andalucía se propone como uno de sus fines esenciales, “reducir las desigualdades en salud y procurar que las personas compartan con equidad los progresos en salud y el bienestar personal y social”. El actual Plan Andaluz de Salud también se propone, como uno de sus objetivos principales, reducir las desigualdades sociales en salud. Como estrategia, plantea realizar estudios de seguimiento sobre las desigualdades sociales en salud, y entre ellas las de género, en el ámbito autonómico. A pesar de estos avances, en Andalucía no disponemos de un sistema de indicadores de salud sensibles al género desagregados a nivel local, que nos permita visualizar y monitorizar la situación de la equidad en este campo y su evolución a lo largo del tiempo. Por ello, se ha elaborado esta “Guía de indicadores para medir las desigualdades de género en salud y sus determinantes”. Sus principales novedades radican en que parte de un marco de los determinantes sociales de la salud y, concretamente, del marco de las desigualdades de género en salud, y que incluye un listado de indicadores para monitorizar estas desigualdades con un nivel de desagregación municipal. Con estas características, la guía se presenta como un recurso de gran utilidad para diseñar políticas y actuaciones a nivel municipal orientadas a reducir las desigualdades de género en salud, facilitando la adecuación de las actuaciones a las necesidades específicas de cada contexto. Esta guía se enmarca dentro de un proyecto de investigación de excelencia denominado “Atlas de las desigualdades de género en salud y sus determinantes sociales en Andalucía”, realizado en la Escuela Andaluza de Salud Pública (Granada, España). Para elaborar este sistema de indicadores y recoger las fuentes de datos disponibles, se ha realizado una consulta a personas expertas siguiendo la técnica Delphi, uno de los métodos de prospectiva con el que se busca generar un consenso en base al análisis de un problema previamente definido. La guía aporta cuatro productos. El primero de ellos es un esquema con una estructura de dimensiones y subdimensiones apropiada para abordar las desigualdades de género en salud y sus determinantes. En segundo lugar, la guía aporta un listado detallado de los indicadores aportados por las personas expertas, clasificados dentro de las dimensiones y subdimensiones que recogía el primer listado. Se incluyen en este listado tanto los indicadores que cuentan con fuentes disponibles para su obtención a nivel local, como los que presentan alguna limitación en la accesibilidad a los datos. En tercer lugar, la guía aporta un listado priorizado de indicadores de género, los que según las personas expertas cuentan con mayor sensibilidad y son más capaces de monitorizar las desigualdades de género en salud y sus determinantes en contextos como el andaluz con un nivel de desagregación municipal. Por último, el cuarto listado aporta, para estos indicadores priorizados, otros detalles de interés para valorar su nivel de sensibilidad y accesibilidad a los datos, así como las fuentes disponibles para su obtención aportadas por las personas expertas. Estos listados pueden ser utilizados para mejorar las estadísticas de contextos como el andaluz, al resultar una potencial herramienta de comparación entre los datos disponibles y los que resultaría conveniente incluir en el futuro. Esperamos que la guía resulte de utilidad y que suponga un avance en la visibilización, monitorización y reducción de las desigualdades de género en salud en nuestro contexto.Este proyecto ha recibido financiación de la Consejería de Economía, Innovación, Ciencia y Empleo de la Junta de Andalucía y del Fondo Europeo de Desarrollo Regional (Expediente P08-CTS-4321)

Social deprivation and exposure to health promotion. A study of the distribution of health promotion resources to schools in England

This article has been made available through the Brunel Open Access Publishing Fund and is available from the specified link - Copyright @ 2010 Chivu and ReidpathBACKGROUND: Area deprivation is a known determinant of health. It is also known that area deprivation is associated with lower impact health promotion. It is less well known, however, whether deprived areas are less responsive to health promotion, or whether they are less exposed. Using data from a national, school-based campaign to promote vaccination against the human papilloma virus (HPV), the relationship between area deprivation and exposure was examined. METHODS: Taking advantage of a health promotion campaign to provide information to schools about HPV vaccination, a cross sectional study was conducted to examine the relationship between area level, social deprivation, and take-up of (i.e., exposure to) available health promotion material. The sample was 4,750 schools across England, including government maintained and independent schools. The relationship between area deprivation and exposure was examined using bi- and multivariate logistic regression. RESULTS: It was found that schools in the least deprived quintile had 1.32 times the odds of requesting health promotion materials than schools in the most deprived areas (p = .01). This effect was independent of the school size, the type of school, and the geographic region. Conclusion The relationship between area deprivation and the impact of health promotion may be due, at least in part, to differential levels of exposure. The study was limited in scope, pointing to the need for more research, but also points to potentially important policy implications

Towns with extremely low mortality due to ischemic heart disease in Spain

BACKGROUND: The cause of coronary disease inframortality in Spain is unknown. The aim of this study is to identify Spanish towns with very low ischemic heart disease mortality, describe their health and social characteristics, and analyze the relationship with a series of contextual factors. METHODS: We obtained the number of deaths registered for each of 8,122 Spanish towns in the periods 1989-1998 and 1999-2003. Expected deaths, standardized mortality ratio (SMR), smoothed Relative Risk (RR), and Posterior Probability (PP) of RR > 1 were calculated using Bayesian hierarchical models. Inframortality was defined as any town that displayed an RR below the 10th percentile, an SMR of under 1 for both sexes, and a PP of RR > 1 less than or equal to 0.002 for male and 0.005 for female mortality, during the two periods covered. All the remaining towns, except for those with high mortality classified as "tourist towns", were selected as controls. The association among socioeconomic, health, dietary, lifestyle and vascular risk factors was analyzed using sequential mixed logistic regression models, with province as the random-effects variable. RESULTS: We identified 32 towns in which ischemic heart disease mortality was half the national rate and four times lower than the European Union rate, situated in lightly populated provinces spread across the northern half of Spain, and revealed a surprising pattern of geographic aggegation for 23 of the 32 towns. Variables related with inframortality were: a less aged population (OR 0.93, 95% CI 0.89-0.99); a contextual dietary pattern marked by a high fish content (OR 2.13, 95% CI 1.38-3.28) and wine consumption (OR 1.50, 95% CI 1.08-2.07); and a low prevalence of obesity (OR 0.47, 95% CI 0.22-1.01); and, in the case of towns of over 1000 inhabitants, a higher physician-population ratio (OR 3.80, 95% CI 1.17-12.3). CONCLUSIONS: Results indicate that dietary and health care factors have an influence on inframortality. The geographical aggregation suggests that other factors with a spatial pattern, e.g., genetic or environmental might also be implicated. These results will have to be confirmed by studies in situ, with objective measurements at an individual level.This study was funded by research study grant no. PI06/0656 from Spain's Health Research Fund (Fondo de Investigación Sanitaria).S

Age adjustment in ecological studies: using a study on arsenic ingestion and bladder cancer as an example

<p>Abstract</p> <p>Background</p> <p>Despite its limitations, ecological study design is widely applied in epidemiology. In most cases, adjustment for age is necessary, but different methods may lead to different conclusions. To compare three methods of age adjustment, a study on the associations between arsenic in drinking water and incidence of bladder cancer in 243 townships in Taiwan was used as an example.</p> <p>Methods</p> <p>A total of 3068 cases of bladder cancer, including 2276 men and 792 women, were identified during a ten-year study period in the study townships. Three methods were applied to analyze the same data set on the ten-year study period. The first (Direct Method) applied direct standardization to obtain standardized incidence rate and then used it as the dependent variable in the regression analysis. The second (Indirect Method) applied indirect standardization to obtain standardized incidence ratio and then used it as the dependent variable in the regression analysis instead. The third (Variable Method) used proportions of residents in different age groups as a part of the independent variables in the multiple regression models.</p> <p>Results</p> <p>All three methods showed a statistically significant positive association between arsenic exposure above 0.64 mg/L and incidence of bladder cancer in men and women, but different results were observed for the other exposure categories. In addition, the risk estimates obtained by different methods for the same exposure category were all different.</p> <p>Conclusions</p> <p>Using an empirical example, the current study confirmed the argument made by other researchers previously that whereas the three different methods of age adjustment may lead to different conclusions, only the third approach can obtain unbiased estimates of the risks. The third method can also generate estimates of the risk associated with each age group, but the other two are unable to evaluate the effects of age directly.</p

Common errors in disease mapping

Abstract. Many morbid-mortality atlases and small-area studies have been carried out over the last decade. However, the methods used to draw up such research, the interpretation of results and the conclusions published are often inaccurate. Often, the proliferation of this practice has led to inefficient decision-making, implementation of inappropriate health policies and negative impact on the advancement of scientific knowledge. This paper reviews the most frequent errors in the design, analysis and interpretation of small-area epidemiological studies and proposes a diagnostic evaluation test that should enable the scientific quality of published papers to be ascertained. Nine common mistakes in disease mapping methods are discussed. From this framework, and following the theory of diagnostic evaluation, a standardised test to evaluate the scientific quality of a small-area epidemiology study has been developed. Optimal quality is achieved with the maximum score (16 points), average with a score between 8 and 15 points, and low with a score of 7 or below. A systematic evaluation of scientific papers, together with an enhanced quality in future research, will contribute towards increased efficacy in epidemiological surveillance and in health planning based on the spatio-temporal analysis of ecological information