Basque Institute for Healthcare Innovation

Sondika, Spain

Basque Institute for Healthcare Innovation

Sondika, Spain
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Orueta J.F.,Basque Health Service | Orueta J.F.,Basque Institute for Healthcare Innovation | Nuno-Solinis R.,Basque Institute for Healthcare Innovation | Mateos M.,Basque Institute for Healthcare Innovation | And 2 more authors.
BMC Health Services Research | Year: 2012

Background: Chronic diseases are an increasing threat to people's health and to the sustainability of health organisations. Despite the need for routine monitoring systems to assess the impact of chronicity in the population and its evolution over time, currently no single source of information has been identified as suitable for this purpose. Our objective was to describe the prevalence of various chronic conditions estimated using routine data recorded by health professionals: diagnoses on hospital discharge abstracts, and primary care prescriptions and diagnoses. Methods. The ICD-9-CM codes for diagnoses and Anatomical Therapeutic Chemical (ATC) codes for prescriptions were collected for all patients in the Basque Country over 14 years of age (n=1,964,337) for a 12-month period. We employed a range of different inputs: hospital diagnoses, primary care diagnoses, primary care prescriptions and combinations thereof. Data were collapsed into the morbidity groups specified by the Johns Hopkins Adjusted Clinical Groups (ACGs) Case-Mix System. We estimated the prevalence of 12 chronic conditions, comparing the results obtained using the different data sources with each other and also with those of the Basque Health Interview Survey (ESCAV). Using the different combinations of inputs, Standardized Morbidity Ratios (SMRs) for the considered diseases were calculated for the list of patients of each general practitioner. The variances of the SMRs were used as a measure of the dispersion of the data and were compared using the Brown-Forsythe test. Results: The prevalences calculated using prescription data were higher than those obtained from diagnoses and those from the ESCAV, with two exceptions: malignant neoplasm and migraine. The variances of the SMRs obtained from the combination of all the data sources (hospital diagnoses, and primary care prescriptions and diagnoses) were significantly lower than those using only diagnoses. Conclusions: The estimated prevalence of chronic diseases varies considerably depending of the source(s) of information used. Given that administrative databases compile data registered for other purposes, the estimations obtained must be considered with caution. In a context of increasingly widespread computerisation of patient medical records, the complementary use of a range of sources may be a feasible option for the routine monitoring of the prevalence of chronic diseases. © 2012 Orueta et al.; licensee BioMed Central Ltd.


Alonso-Moran E.,Basque Institute for Healthcare Innovation | Satylganova A.,European Master in Sustainable Regional Health Systems | Nuno-Solinis R.,Basque Institute for Healthcare Innovation
BMC Public Health | Year: 2014

Background: The aim of the study was to estimate the prevalence of depression in the population diagnosed with diabetes type 2 and to test the hypothesis that the presence of depression in such cases was associated with a) worse glycaemic control, and b) higher healthcare costs. Methods. We conducted a cross-sectional analysis, from 1st September 2010 to 31st August 2011, among patients with type 2 diabetes aged 35 years and over in the Basque Country. It was identified how many of them had also depression. The database included administrative individual level information on age, sex, healthcare costs, other comorbidities, and values of glycaemic control (HbA1c). Deprivation index variable was used as socioeconomic measure and, to observe the coexistent pathologies, all the patients diagnoses were categorized by Adjusted Clinical Groups. We used a measure of association, a logistic and a linear regression for analysis. Results: 12.392 (9.8%) of type 2 diabetes patients were diagnosed with depression, being the prevalence 5.2% for males and 15.1% for females. This comorbidity was higher among the most deprived population. There was no association between the presence of depression and glycaemic control. We estimated that the comorbidity average cost per patient/year was 516 higher than in patients with just type 2 diabetes (P < 0.001) adjusted by the other covariates. Conclusions: We did not find any relationship between depression and glycaemic control in patients with type 2 diabetes. However, the comorbidity was associated with significantly high healthcare costs compared to that of type 2 diabetes occurring alone, after adjusting by other illness. Thus, there is a need of more precise recognition, screening and monitoring of depression among diabetic population. Evidence-based treatment for depression should be included in type 2 diabetes clinical guidelines. © 2014 Alonso-Morán et al.; licensee BioMed Central Ltd.


Orueta J.F.,Basque Institute for Healthcare Innovation | Nuno-Solinis R.,Basque Institute for Healthcare Innovation | Garcia-Alvarez A.,Research Center en Cronicidad | Alonso-Moran E.,Basque Institute for Healthcare Innovation
BMC Public Health | Year: 2013

Background: Multimorbidity is clearly a major challenge for healthcare systems. However, currently, its magnitude and impact on healthcare expenditures is still not well known. The objective of this paper is to present an overview of the prevalence of multimorbidity by deprivation level in the elderly population of the Basque Country. Methods. We conducted a cross-sectional analysis that included all the inhabitants of the Basque Country aged 65 years and over (N = 452,698). This was based on data from primary care electronic medical records, hospital admissions, and outpatient care databases, for a 4-year period. The health problems of the patients were identified from their diagnoses and prescriptions. Multimorbidity was defined as the presence of two or more chronic diseases out of a list of 47 of the most important and common chronic conditions consistent with the literature. In addition, we explored socio-economic and demographic variables such as age, sex, and deprivation level. Results: Multimorbidity was found in 66.13% of the population aged 65 and over and increases with age until 80 years. The prevalence of multimorbidity was higher in deprived (69.94%) than better-off (60.22%) areas. This pattern of differences between the most and least disadvantaged areas was observed in all age groups and more marked in female (70.96-59.78%) than in male (68.54-60.86%) populations. In almost all diseases studied (43 out of 47), 90% of patients had been diagnosed with at least one other illness. It was also frequent the coexistence of mental and physical health problems in the same person and the presence of multiple physical diseases is higher in patients with mental disease than in the rest of population (74.97% vs. 58.14%). Conclusion: Multimorbidity is very common among people over 65 years old in the Basque Country, particularly in unfavourable socioeconomic environments. Given the ageing population, multimorbidity and its consequences should be taken into account in healthcare policy, organization of care and medical research. Administrative health databases are readily available sources of a range of information that can be useful for such purposes. © 2013 Orueta et al.; licensee BioMed Central Ltd.


Orueta J.F.,Basque Health Service | Nuno-Solinis R.,Basque Institute for Healthcare Innovation | Mateos M.,Basque Institute for Healthcare Innovation | Vergara I.,Basque Health Service | Grandes G.,Basque Health Service
BMC Health Services Research | Year: 2013

Background: An increase in chronic conditions is currently the greatest threat to human health and to the sustainability of health systems. Risk adjustment systems may enable population stratification programmes to be developed and become instrumental in implementing new models of care.The objectives of this study are to evaluate the capability of ACG-PM, DCG-HCC and CRG-based models to predict healthcare costs and identify patients that will be high consumers and to analyse changes to predictive capacity when socio-economic variables are added. Methods. This cross-sectional study used data of all Basque Country citizens over 14 years of age (n = 1,964,337) collected in a period of 2 years. Data from the first 12 months (age, sex, area deprivation index, diagnoses, procedures, prescriptions and previous cost) were used to construct the explanatory variables. The ability of models to predict healthcare costs in the following 12 months was assessed using the coefficient of determination and to identify the patients with highest costs by means of receiver operating characteristic (ROC) curve analysis. Results: The coefficients of determination ranged from 0.18 to 0.21 for diagnosis-based models, 0.17-0.18 for prescription-based and 0.21-0.24 for the combination of both. The observed area under the ROC curve was 0.78-0.86 (identifying patients with a cost higher than P-95) and 0.83-0.90 (P-99). The values of the DCG-HCC models are slightly higher and those of the CRG models are lower, although prescription information could not be used in the latter. On adding previous cost data, differences between the three systems decrease appreciably. Inclusion of the deprivation index led to only marginal improvements in explanatory power. Conclusion: The case-mix systems developed in the USA can be useful in a publicly financed healthcare system with universal coverage to identify people at risk of high health resource consumption and whose situation is potentially preventable through proactive interventions. © 2013 Orueta et al.; licensee BioMed Central Ltd.


Garcia-Alvarez A.,Basque Institute for Healthcare Innovation | Garcia-Goni M.,Complutense University of Madrid | Paolucci F.,Australian National University | Paolucci F.,Northumbria University | Nuno-Solinis R.,Basque Institute for Healthcare Innovation
PLoS ONE | Year: 2014

Background: Multimorbidity is a major challenge for healthcare systems. However, currently, its magnitude and impact in healthcare expenditures is still mostly unknown. Objective: To present an overview of the prevalence and costs of multimorbidity by socioeconomic levels in the whole Basque population. Methods: We develop a cross-sectional analysis that includes all the inhabitants of the Basque Country (N = 2,262,698). We utilize data from primary health care electronic medical records, hospital admissions, and outpatient care databases, corresponding to a 4 year period. Multimorbidity was defined as the presence of two or more chronic diseases out of a list of 52 of the most important and common chronic conditions given in the literature. We also use socioeconomic and demographic variables such as age, sex, individual healthcare cost, and deprivation level. Predicted adjusted costs were obtained by log-gamma regression models. Results: Multimorbidity of chronic diseases was found among 23.61% of the total Basque population and among 66.13% of those older than 65 years. Multimorbid patients account for 63.55% of total healthcare expenditures. Prevalence of multimorbidity is higher in the most deprived areas for all age and sex groups. The annual cost of healthcare per patient generated for any chronic disease depends on the number of coexisting comorbidities, and varies from 637 € for the first pathology in average to 1,657 € for the ninth one. Conclusion: Multimorbidity is very common for the Basque population and its prevalence rises in age, and unfavourable socioeconomic environment. The costs of care for chronic patients with several conditions cannot be described as the sum of their individual pathologies in average. They usually increase dramatically according to the number of comorbidities. Given the ageing population, multimorbidity and its consequences should be taken into account in healthcare policy, the organization of care and medical research. © 2014 Orueta et al.


Nuno-Solinis R.,Basque Institute for Healthcare Innovation | Orueta J.F.,Basque Health Service | Mateos M.,Basque Institute for Healthcare Innovation
Journal of Ambulatory Care Management | Year: 2012

Chronic conditions have an impact on individuals since they represent a restraint on quality of life, functional status, and productivity of people who suffer from them but they also compromise the sustainability of health systems. In 2010, the Strategy for Tackling the Challenge of Chronicity in the Basque Country was published. It contains policies and projects aimed at reinventing the health delivery model with the purpose of improving the quality of care for chronic patients and advancing toward a more sustainable, proactive, and integrated model. We present 3 projects here: population stratification, integrated care initiatives, and innovation from health care staff. Copyright © 2012 Wolters Kluwer Health | Lippincott Williams & Wilkins.


Nuno R.,Basque Institute for Healthcare Innovation | Coleman K.,MacColl Institute for Healthcare Innovation | Bengoa R.,Donostia International Physics Center | Sauto R.,Basque Institute for Healthcare Innovation
Health Policy | Year: 2012

Objective: The aim of this research is to highlight the current relevance of the Innovative Care for Chronic Conditions (ICCC) Framework, as a model for change in health systems towards better care for chronic conditions, as well as to assess its impact on health policy development and healthcare redesign to date. Methods: The authors reviewed the literature to identify initiatives designed and implemented following the ICCC Framework. They also reviewed the evidence on the effectiveness, cost-effectiveness and feasibility of the ICCC and the earlier Chronic Care Model (CCM) that inspired it. Results: The ICCC Framework has inspired a wide range of types of intervention and has been applied in a number of countries with diverse healthcare systems and socioeconomic contexts. The available evidence supports the effectiveness of this framework's components, although no study explicitly assessing its comprehensive implementation at a health system level has been found. Conclusions: As awareness of the need to reorient health systems towards better care for chronic patients grows, there is great potential for the ICCC Framework to serve as a road map for transformation, with its special emphasis on integration, and on the role of the community and of a positive political environment. © 2011 Elsevier Ireland Ltd.


Molina E.H.,11 Health | Nuno-Solinis R.,Basque Institute for Healthcare Innovation | Idioaga G.E.,Association for the Promotion of Innovation DENOKINN | Flores S.L.,11 Health | And 2 more authors.
BMC Palliative Care | Year: 2013

Background: SAIATU is a program of specially trained in-home social assistance and companionship which, since February 2011, has provided support to end-of-life patients, enabling the delivery of better clinical care by healthcare professionals in Osakidetza (Basque Health Service), in Guipúzcoa (Autonomous Community of the Basque Country).In January 2012, a retrospective observational study was carried out, with the aim of describing the characteristics of the service and determining if the new social service and the associated socio-health co-ordination had produced any effect on the use of healthcare resources by end-of-life patients.The results of a comparison of a cohort of cases and controls demonstrated evidence that the program could reduce the use of hospital resources and promote the continuation of living at home, increasing the home-based activity of primary care professionals.The objective of this study is to analyse whether a program of social intervention in palliative care (SAIATU) results in a reduction in the consumption of healthcare resources and cost by end-of-life patients and promotes a shift towards a more community-based model of care. Method/design. Comparative prospective cohort study, with randomised selection of patients, which will systematically measure patient characteristics and their consumption of resources in the last 30 days of life, with and without the intervention of a social support team trained to provide in-home end-of-life care.For a sample of approximately 150 patients, data regarding the consumption of public healthcare resources, SAIATU activity, home hospitalisation teams, and palliative care will be recorded. Such data will also include information dealing with the socio-demographic and clinical characteristics of the patients and attending carers, as well as particular characteristics of patient outcomes (Karnofsky Index), and of the outcomes of palliative care received (Palliative Outcome Scale).Ethical approval for the study was given by the Clinical Research Ethics Committee of Euskadi (CREC-C) on 10 Dec 2012. Discussion. The results of this prospective study will assist in verifying or disproving the hypothesis that the in-home social care offered by SAIATU improves the efficiency of healthcare resource usage by these patients (quality of life, symptom control).This project represents a dramatic advance with respect to other studies conducted to date, and demonstrates how, through the provision of personnel trained to provide social care for patients in the advanced stages of illness, and through strengthening the co-ordination of such social services with existing healthcare system resources, the resulting holistic structure obtains cost savings within the health system and improves the efficiency of the system as a whole. © 2013 Molina et al.


Nuno-Solinis R.,Basque Institute for Healthcare Innovation | Rodriguez-Pereira C.,Basque Institute for Healthcare Innovation | Alonso-Moran E.,Basque Institute for Healthcare Innovation | Orueta J.F.,Astrabudua Health Center
Journal of Osteoporosis | Year: 2014

Objectives. This study aimed to establish the prevalence of multimorbidity in women diagnosed with osteoporosis and to report it by deprivation index. The characteristics of comorbidity in osteoporotic women are compared to the general female chronic population, and the impact on healthcare expenditure of this population group is estimated. Methods. A cross-sectional analysis that included all Basque Country women aged 45 years and over (N = 579,575) was performed. Sociodemographic, diagnostic, and healthcare cost data were extracted from electronic databases for a one-year period. Chronic conditions were identified from their diagnoses and prescriptions. The existence of two or more chronic diseases out of a list of 47 was defined as multimorbidity. Results. 9.12% of women presented osteoporosis and 85.04% of them were multimorbid. Although multimorbidity in osteoporosis increased with age and deprivation level, prevalence was higher in the better-off groups. Women with osteoporosis had greater risk of having other musculoskeletal disorders but less risk of having diabetes (RR = 0.65) than chronic patients without osteoporosis. People with poorer socioeconomic status had higher healthcare cost. Conclusions. Most women with osteoporosis have multimorbidity. The variety of conditions emphasises the complexity of clinical management in this group and the importance of maintaining a generalist and multidisciplinary approach to their clinical care. © 2014 Roberto Nuño-Solinis et al.


Alonso-Moran E.,Basque Institute for Healthcare Innovation | Nuno-Solinis R.,Basque Institute for Healthcare Innovation | Onder G.,Catholic University of the Sacred Heart | Tonnara G.,Catholic University of the Sacred Heart
European Journal of Internal Medicine | Year: 2015

Introduction Risk stratification tools were developed to assess risk of negative health outcomes. These tools assess a variety of variables and clinical factors and they can be used to identify targets of potential interventions and to develop care plans. The role of multimorbidity in these tools has never been assessed. Objectives To summarize validated risk stratification tools for predicting negative outcomes, with a specific focus on multimorbidity. Methods MEDLINE, Cochrane Central Register of Controlled Trials and PubMed database were interrogated for studies concerning risk prediction models in medical populations. Review was conducted to identify prediction models tested with patients in both derivation and validation cohorts. A qualitative synthesis was performed focusing particularly on how multimorbidity is assessed by each algorithm and how much this weighs in the ability of discrimination. Results Of 3674 citations reviewed, 36 articles met criteria. Of these, 29 had as outcome hospital admission/readmission. The most common multimorbidity measure employed in the models was the Charlson Comorbidity Index (12 articles). C-statistics ranged between 0.5 and 0.85 in predicting hospital admission/ readmission. The highest c-statistics was 0.83 in models with disability as outcome. For healthcare cost, models which used ACG-PM case mix explained better the variability of total costs. Conclusions This review suggests that predictive risk models which employ multimorbidity as predictor variable are more accurate; CHF, cerebro-vascular disease, COPD and diabetes were strong predictors in some of the reviewed models. However, the variability in the risk factors used in these models does not allow making assumptions. © 2015 European Federation of Internal Medicine.Published by Elsevier B.V. All rights reserved.

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