Building Bridges for Innovation in Ageing: Synergies between Action Groups of the EIP on AHA.

The Strategic Implementation Plan of the European Innovation Partnership on Active and Healthy Ageing (EIP on AHA) proposed six Action Groups. After almost three years of activity, many achievements have been obtained through commitments or collaborative work of the Action Groups. However, they have often worked in silos and, consequently, synergies between Action Groups have been proposed to strengthen the triple win of the EIP on AHA. The paper presents the methodology and current status of the Task Force on EIP on AHA synergies. Synergies are in line with the Action Groups' new Renovated Action Plan (2016-2018) to ensure that their future objectives are coherent and fully connected. The outcomes and impact of synergies are using the Monitoring and Assessment Framework for the EIP on AHA (MAFEIP). Eight proposals for synergies have been approved by the Task Force: Five cross-cutting synergies which can be used for all current and future synergies as they consider overarching domains (appropriate polypharmacy, citizen empowerment, teaching and coaching on AHA, deployment of synergies to EU regions, Responsible Research and Innovation), and three cross-cutting synergies focussing on current Action Group activities (falls, frailty, integrated care and chronic respiratory diseases).

Global health care use by patients with type-2 diabetes: Does the type of comorbidity matter?

AIM: To identify patterns of health care use among diabetic patients with multimorbidity across primary, specialised, hospital and emergency care, depending on their type of chronic comorbidity. METHODS: Longitudinal study of a population-based retrospective cohort conformed by adult patients with type-2 diabetes assigned to any of the primary care centres in Aragon during 2010 and 2011 (n=65,716). Negative binomial regressions were run to model the effect of the type of comorbidity on the number of visits to each level of care. Comorbidities were classified as concordant, discordant or mental based on expert consensus and depending on whether they shared the same overall pathophysiologic risk profile and disease management plan designed for type-2 diabetes. RESULTS: Mental comorbidity was independently associated with total and unplanned admissions (incidence rate ratio [IRR]:1.25; 95% confidence interval [CI]:1.12-1.39, IRR:1.21; 95% CI:1.06-1.39), average length of stay (IRR:1.47; 95% CI:1.25-1.73), and total and priority emergency room visits (IRR:1.26; 95% CI:1.17-1.35, IRR:1.30; 95% CI:1.18-1.42). Patients with discordant comorbidities showed the strongest associations with the number of visits to specialists (IRR:1.38; 95% CI:1.33-1.43) and to different specialties (IRR:1.36; 95% CI:1.32-1.39). Differences regarding GP visits were lower but still significant for patients with discordant comorbidity (IRR:1.08; 95% CI:1.06-1.11), but especially for those with mental comorbidity (IRR:1.17; 95% CI:1.14-1.21). CONCLUSION: In patients with type-2 diabetes, the coexistence of mental comorbidity significantly increases the use of unplanned hospital services, and discordant comorbidities have an important effect on specialised care use. Differences with respect to primary care use are not as prominent.

Does higher quality of primary healthcare reduce hospital admissions for diabetes complications? A national observational study.

AIM: To determine if hospital admission rates for diabetes complications (acute complications, chronic complications, no complications and hypoglycaemia) were associated with primary care diabetes management. METHODS: We performed an observational study in the population in England during the period 2004-2009 (54 741 278 people registered with 8140 general practices). We used multivariable negative binomial regression to model the associations between indirectly standardized hospital admission rates for complications and primary healthcare quality, supply and access indicators, diabetes prevalence and population factors. RESULTS: In multivariate regression models, increasing deprivation (incidence rate ratio: 1.0154; P < 0.001, 95% CI 1.0141-1.0166) and diabetes prevalence (incidence rate ratio: 1.0956; P < 0.001, 95% CI 1.0677-1.1241) were risk factors for admission, while most healthcare covariates, i.e. a larger practice population (incidence rate ratio 0.9999, P = 0.013, 95% CI 0.9999-0.9999), better patient-perceived urgent and non-urgent access to primary care (incidence rate ratio: 0.9989, P = 0.023; 95% CI 0.9979-0.9998 and incidence rate ratio: 0.9988; P = 0.003, 95% CI 0.9980-0.9996, respectively) and better HbA1c target achievement (incidence rate ratio: 0.9971; P < 0.001, 95% CI 0.9958-0.9984), were protective. Diabetes admissions decreased significantly during the period 2004-2009. CONCLUSIONS: After controlling for population factors, better scheduled primary care access and glycaemic control were associated with lower hospital admission rates across most complications. There is little rationale to restrict primary care-sensitive condition definitions to acute complications. They should be revised to improve the usefulness of hospital admission data as an outcome measure, and to facilitate international comparisons. The risk of emergency hospital admission should be monitored routinely.

Morbilidad y coste asociado a los trastornos neurológicos / Morbidity and costs associated with neurological disorders

No disponible

Evaluación de la Gestión Clínica y sus resultados. Modelo consensuado y diseñado en el Hospital Clínico de Zaragoza / Clinical Management assessment and its results. Consensual model designed at the Clincial Hospital of Zaragoza

Es razonable incentivar el uso adecuado de los recursos, la mejora de la práctica clínica y de la salud de las personas, a un coste que la sociedad pueda asumir. Para ello deben diseñarse sistemas de incentivos que estén basados en el consenso y la participación suficientes por parte de los profesionales. En el año 2000 la Comisión Mixta del Hospital Clínico Universitario de Zaragoza (HCU) tomó la decisión de diseñar un modelo de evaluación de la gestión clínica de los Servicios que permitiese con su aplicación repartir la productividad en función de los resultados alcanzados a fin de año. Ese modelo de evaluación está basado fundamentalmente en indicadores de actividad, calidad y costes. Y ha sido utilizado desde entonces, en el HCU de Zaragoza para el reparto anual de la productividad de forma variable (AU)

In this work, the authors present the results of the Mixed Commission of the University Clinical Hospital of Zaragoza which, in 2000, designed an assessment model for the clinical management of the Services which, with its application, makes it possible to distribute productivity according to the results obtained (AU)

Experiencia en la asignación de la productividad de forma variable en el Hospital Clínico Universitario de Zaragoza / Experience in the alocation of variable productivity in the University Hospital Clinic of Zaragoza

Desde el año 2000 el Hospital Clínico Universitario de Zaragoza (HCU) viene utilizado un modelo de evaluación de la gestión clínica, diseñado por el propio centro, para el reparto de la productividad anual de forma variable en función de los resultados alcanzados por cada servicio a fin de año. Este método de evaluación e incentivación ha representado importantes cambios en la cultura de gestión de los profesionales, incrementando el interés por el seguimiento de los indicadores y por los resultados obtenidos así como un mayor compromiso con los acuerdos de gestión. A pesar de haber existido diferencias importantes entre la cuantías percibidas entre Servicios, el modelo ha sido bien aceptado y no ha generado ningún tipo de conflicto ya que se ha basado en a transparencia y el consenso de la metodología utilizada (AU)

This article presents a clinical management assessment model, designed by the University Hospital Clinic of Zaragoza, to obtain a distribution of the annual variable productivity according to the results achieved by each service at the end of the year (AU)

Validación de un instrumento para evaluar el funcionamiento y repartir incentivos entre los servicios de un hospital / Validation of an instrument to assess functioning and distribute incentives among the services of a hospital

Objetivo: Diseñar y examinar la fiabilidad de una herramienta para evaluar los resultados y distribuir incentivos entre los servicios del hospital. Material y Métodos: Se definieron de forma explícita las características de la herramienta de evaluación (representatividad, transparencia, claridad, pertinencia, accesibilidad, veracidad, carácter reproducible, sensibilidad, especificidad, estabilidad, eficiencia y aceptación) y se utilizaron dichos criterios para seleccionar indicadores y desarrollar los modelos de evaluación específicos de cada servicio. Para validar el método se midió su precisión (coherencia intra e interobservador, coeficiente de variación y bondad de ajuste a la normal) y su validez de contenido, de construcción y de criterio con respecto a una encuesta de opinión previa entre el equipo directivo (correlación de Pearson e índice Kappa). Resultados: La herramienta desarrollada constaba de 15 modelos de evaluación elaborados a partir de 49 indicadores (31 de actividad, cuatro de costes y 14 de calidad asistencial). Se evaluaron 56 unidades aistenciales, cuya calificación media fue de 73,5 ñ 18,1 puntos, con un mínimo de 29 y un máximo de 100. En Actividad la puntuación media fue de 52,1 ñ 14,7 sobre 70, en Costes de 13,7 ñ 7,4 sobre 20 y en Calidad de 7,6 ñ 2,1 sobre 10. El modelo se ajustaba a una distribución normal, con un CV de 0,25, un error intraobsevador de 0,25 por ciento e interobservador del 0,48 por ciento. La correlación con la opinión del equipo directivo era positiva (r = 0,43 p = 0,004), pero los índices de concordancia kappa eran bajos (0,21). Conclusiones: El método de evaluación probado es preciso, está bien construido y tiene una aparente validez de criterio. Queda ahora por demostrar si sirve para mejorar los resultados y la calidad de la asistencia prestada (AU)

Herramientas de medida del producto sanitario en la asistencia a urgencias y emergencias / The need to use tools to measure the medical product at emergency care units

No disponible

No disponible

[A retrospective evaluation of the behaviour of groups under out-patient care at a health center]. / Evaluación retrospectiva del comportamiento de los grupos de cuidados ambulatorios en un centro de salud.

OBJECTIVES: To study and analyse the Out-Patient Care Groups (OCGs), and evaluate how they affect use of health resources. DESIGN: An observational, retrospective study. SETTING: Ciudad Jardín Health Centre, Málaga. PARTICIPANTS: 2999 patients with a clinical history opened before 31.12.95, chosen from 5 of the 17 medical lists at the Health Centre, were included. RESULTS: The statistical analysis was performed with the SPSS software package of the Calculation Centre at Málaga University. A descriptive test produced the following results: 33% of the patients were classified in OCG 41 (combination of 2 or 3 out-patient diagnosis groups in people over 34); 19% belonged to groups of stable or unstable chronic illnesses (OCGs 8, 9 and 10); and 9% had acute children's diseases. Then multiple regression constructed a model with the OCGs as independent variable and annual visits, further tests performed and referral to specialists as dependent variables. In this model the OCGs were able to explain 20.3% of resource consumption. CONCLUSIONS: In the retrospective study and with a limited sample of 2999 patients, the OCGs are able to explain 20.3% of resource consumption. However, it does seem a valid model for discriminating between normal and over-using patients.

The influence of psychological and social factors on accuracy of self-reported blood pressure.

The data reported here document levels of accuracy in reports of blood pressure and identify correlates of inaccurate reporting. The data come from a long-term follow-up of a cohort of African-American women who registered for antepartum care between September, 1967 and June, 1969. At the follow-up interview, these women were asked whether they had ever received a diagnosis of hypertension from a physician. The self-reports of hypertension were compared with information contained in the medical records of these women. Twenty-five percent reported having high blood pressure but 53% of these reports were unconfirmed by their medical records (overall misreporting rates was 15.9% with 2.5% underreporting and 13.4% overreporting). The factors related to misreporting included a psychiatric diagnosis (based on the Diagnostic Interview Schedule) of major depressive disorder or drug and/or alcohol abuse and a small social network. The conjunction of these three variables significantly affected accuracy of reporting (100% misreporting with all three variables). These results suggest that, using currently standard methodology, there is an unreliable subpopulation of respondents in health surveys that may require the collection of data on health status from a second source to confirm data from self-reported health measures.

[Characteristics of non-responders in a follow-up study of those over 65 years of age]. / Características de los no respondientes a un estudio de seguimento en mayores de 65 años.

The best way to estimate non response bias and its potential effect in epidemiological research to know the characteristics of non respondents. The purpose of this study is to analyze what characteristics of those who refused to answer telephone and personal interviews in a follow-up study can predict non-response. As part of the Yale Health and Ageing Project, a follow-up study initiated in 1982 in the USA in a population sample of 2.806 over 65 years of age, the influence of several factors in non-response rate for those who refused to answer the interview was analyzed. A total of 21 variables related to demographic, health, and social characteristics were analyzed. The dependent variable was defined as response/non-response to the interviews. The results did not show significant statistical associations. The only factors that showed specific patterns were housing (in both types of interviews), and education level, cognitive status, and physical disability in personal interview in women, with p values for the Odds Ratios between 0.05 and 0.07. In conclusion, most results of this study do not support the findings already published. A disadvantaged sociodemographic situation was not a predictor factor of non-response, except for the education level of women in personal interviews. In relation to health status only a poor cognitive status, as it has been already reported, seems to induce refusal of women to personal interviews.