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Background: The large number of dementia cases produces a great pressure on health and social care services, which requires efficient planning to meet the needs of patients through infrastructure, equipment, and financial, technical, and personal resources adjusted to their demands. Dementia analysis requires studies with a very precise patient characterization of both the disease and comorbidities present, and long-term follow-up of patients in clinical aspects and patterns of resource utilization and costs generated. Objective: To describe and quantify direct healthcare expenditure and its evolution from three years before and up to ten years after the diagnosis of dementia, compared to a matched group without dementia. Methods: Retrospective cohort design with follow-up from 6 to 14 years. We studied 996 people with dementia (PwD) and 2,998 controls matched for age, sex, and comorbidity. This paper adopts the provider's perspective as the perspective of analysis and refers to the costs actually incurred in providing the services. Aggregate costs and components per patient per year were calculated and modelled. Results: Total health expenditure increases in PwD from the year of diagnosis and in each of the following 7 years, but not thereafter. Health status and mortality are factors explaining the evolution of direct costs. Dementia alone is not a statistically significant factor in explaining differences between groups. Conclusion: The incremental direct cost of dementia may not be as high or as long as studies with relatively short follow-up suggest. Dementia would have an impact on increasing disease burden and mortality. [ABSTRACT FROM AUTHOR]

Introduction: Serveis de Salut Integrats Baix Empordà, SSIBE (Integrated Health Services Baix Empordà) is a healthcare organization which provides primary, acute and chronic care to a population of 130,000 inhabitants (17% aged 65 and over) in Catalonia, Spain. SSIBE put into effect a Proactive Attention Programme for patients with chronic, complex conditions in 2011. The population was identified as Chronic Complex Patient (CCP) by a predictive model which was based on health status (provided by Clinical Risk Group -CRG- system), pharmaceutical expenditure, and utilization of health resources. The interventions of the programme were: 1-Identification label (2011): it was available in the electronic medical record to identify CCP; 2-CCP lists (2012): delivered to primary doctors encouraging them to do a proactive attention; 3-CCP Day Hospital (2012): it was put into effect for preventing emergency admissions; 4-Shared Individual Intervention Plan (2012) health professionals wrote down physical, psychic, and social necessities of the patients. 5-Support Programme for Discharges (from 2010 to 2013): specialised care notified primary care of discharges;. In order to carry out the evaluation of the programme we grouped the target population into three groups randomly: the Partial Intervention Group (PIG): interventions 1 and 3-5 were applied; the Total Intervention Group (TIG): interventions from 1 to 5 were applied; and the Control Group (CG), usual care. Previously, we assessed the processes and clinical effectiveness of the programme and the findings didn't show relevant differences among groups. That encouraged us to close the whole evaluation process through an economic evaluation to measure the economic impact of it. Theory / Methods: The objectives were: to determine which intervention group was the better option, to obtain basic information about costs and how these had evolved in time horizon; and to know better the consumption patterns of the interventions groups in the integration context. Method: economic evaluation - minimization-cost analysis. Catchment: 4 areas in Baix Empordà managed by SSIBE. Population target: 6,490 patients aged 18 and over. Time horizon: 2011 (zero year); 2012 (put into effect of the interventions); 2013 (consolidation of the programme). Perspective from analysis: 1) activity, individual contacts (visits, admissions, re-admissions, medical sessions, etc.) of patients done during the time horizon, and 2) costs, the activity expressed in monetary units. Both perspectives had the following approaches: - Annual analysis: it was considered the annual activity of target population. - Time-series analysis: it was considered the whole activity of non-exitus population who were assigned to the same group each year. Results: For the zero year, the per-capita cost (net of drug cost) was: CG: 2.300€, PIG: 2.500€, and TIG: 2.540€. For the following years, it increased in CG / TIG while in PIG, it decreased only in 2012. For the time-series, the per-capita cost increased in all groups. The range cumulative variation of percentage was: PIG: 20%; CG: 31%, TIG: 35%. Approximately 60% of patients with chronic, complex conditions needed one or two resources. Nearly 35% needed from three to four resources and only the 2% of them needed all resources available. Discussion: In spite of our findings which are similar to ones of the other research, we know better how the cost has change over time and which combination of resources was more common among all those with chronic, complex conditions. Conclusion: Nonetheless the per-capita cost increased in all groups during the time analysed, there is not a clear evidence to determine which intervention group is the better option. 1. Key findings to date: The factors which could have increased the per-capita cost can be: the exacerbations suffered by patients, the combination of three or more health resources, the major complexity of patients treated. 2. Lessons learned: To know about the consumption patterns of the patients can be a clue when we decide to put into effect health programmes. 3. Limitations: The factors which could have affected the programme can be the organizational culture, the behaviour consumption of patients, the time to consolidate the interventions of the programme, and the external factors such as economic crisis. 4. Future research: The consumption patterns of all those with chronic, complex problems could be a key to understand better how the integration, coordination context works. [ABSTRACT FROM AUTHOR]

Objective: To assess the effectiveness of a proactive and integrated care programme to adjust the use of health resources by chronic complex patients (CCP) identified as potential high consumers according to a predictive model based on prior use and morbidity., Methods: Randomized controlled clinical trial with three parallel groups of CCP: a blinded control group (GC), usual care; a partial intervention group (GIP) reported in the EMR; a total intervention group (GIT), also reported to primary care (PC). Conducted in an integrated health care organization (IHCO), N=128,281 individuals in 2011. Dependent variables: PC visits, emergency attention, hospitalizations, pharmaceutical cost and death., Independent Variables: intervention group, age, sex, area of residence, morbidity (by clinical risk group) and recurrence as CCP., Statistical Analysis: ANOVA, student's t test; logistic and multiple linear regressions at the 95% confidence level., Results: 4,236 CCP included for the first intervention year and 4,223 for the second; recurrence as CCP 72%. Mean age 73.2 years, 54.2% women and over 70% with 2 or more chronic diseases. The number of PC visits was significantly higher for GIT than for GIP and GC. The hospital stays were significantly lower in GIP. This effect was observed in the first year and in the second year only in the new CCP. The general indicators of the IHCO were good, before and during the intervention., Conclusions: A high standard of quality, previous and during the study, and the inevitable contamination between groups, hindered the assessment of the marginal effectiveness of the program., (Copyright © 2016 SESPAS. Publicado por Elsevier España, S.L.U. All rights reserved.)

Objective: To describe the characteristics of a diabetic population, morbidity profile, resource consumption, complications and degree of metabolic control., Design: Cross-sectional study during 2010., Location: Four Health Areas (91.301 people) where the integrated management organization Serveis de Salut integrated Baix Empordà completely provide healthcare assistance., Participants: 4.985 diabetic individuals, identified through clinical codes using the ICD-9-MC classification and the 3M? Clinical Risk Groups software., Main Measurements: Morbidity profile, related complications and degree of metabolic control were obtained for the target diabetic population. We analyzed the consumption of healthcare resources, pharmaceutical and blood glucose reagent strips. All measurements obtained at individual level., Results: 99.3% of the diabetic population were attended at least once at a primary care center (14.9% of visits). 39.5% of primary care visits and less than 10% of the other scanned resources were related to the management of diabetes. The pharmaceutical expenditure was 25.4% of the population consumption (average cost ?1.014,57). 36.5% of diabetics consumed reagents strips (average cost ?120,65). The more frequent CRG are 5424-Diabetes (27%); 6144-Diabetes and Hypertension (25,5%) and 6143-Diabetes and Other Moderate Chronic Disease (17,2%). The degree of disease control is better in patients not consumers of antidiabetic drugs or treated with oral antidiabetic agents not secretagogues., Conclusions: Comorbidity is decisive in the consumption of resources. Just a few part of this consumption is specifically related to the management of diabetes. Results obtained provide a whole population approach to the main existing studies in our national and regional context., (Copyright © 2012 Elsevier España, S.L. All rights reserved.)

Introduction: Understanding the quality, costs and outcomes of healthcare services requires precise determination of the morbidity in a population. Measurement of morbidity in a population and its association with the services provided remains to be performed. The aim of this article was to present our experience of using clinical risk groups (CRGs) to measure morbidity in an integrated healthcare organization (IHO)., Methods: We studied the population attended by an IHO in a county (approximately 120,000 patients) from 2002 to 2005. CRGs were used to measure morbidity. A descriptive analysis was performed of the population's distribution in CRG categories and utilization rates., Results: One or more chronic diseases was found in 15.5% of the population, significant acute illness was found in 9%, minor chronic diseases was found in 7% and very severe diseases was found in 0.5%. Between 2002 and 2005, the number of individuals with chronic disease increased by 8%. The burden of illness increased with age. However, at all ages, at least 40% of the population remained healthy. Comorbidity in chronic illnesses was a crucial factor in explaining healthcare resource utilization., Conclusions: The CRG grouping system aids analysis at different levels for clinical administration. Due to its composition, this system allows better understanding of the use, costs and quality of the set of services received by a population.