Background:Chronicity, and particularly complex care needs for people with chronic diseases is one of the main challenges of health systems.Objective:To determine the population prevalence of people with chronic diseases and complex care needs and to characterize these needs considering features of health and social complexity in Primary Care.Design:Cross-sectional population-based study.Scope:Patients who have one or more chronic health conditions from three Primary Care urban centres of a reference population of 43.647 inhabitants older than 14 years old.Methodology:Data will be obtained from the review of electronical medical records. Complexity will be defined by: 1) the independent clinical judgment of primary care physicians and nurses and 2) the aid of three complexity domains (clinical and social). Patients with advanced chronic disease and limited life prognosis will be also described.Conclusions:This research protocol intends to describe and analyse complex care needs from a primary care professional perspective in order to improve knowledge of complexity beyond multimorbidity and previous consumption of health resources. Knowing about health and social complexity with a more robust empirical basis could help for a better integration of social and health policies and a more proactive and differentiated care approach in this most vulnerable population.

Objective: Characterize subgroups of Complex Chronic Patients (CCPs) with cluster analysis from the general practitioner's perspective. Study design:Cross-sectional population-based study.Setting: Three Primary Care urban centres for a reference population of 43,647 inhabitants over 14 years old in Sabadell, Catalonia, Spain. Methods:Complexity is defined by the independent clinical judgment of general practitioners with the aid of complexity domains (both clinical and social). We used a Two-Step Cluster method to identify relevant subgroups of CCPs.Results: Three relevant subgroups were identified. The first one was mainly managed by primary care professionals, and 63% of its CCPs belonged to the high-risk stratum of the Adjusted Morbidity Groups (GMA). The second subgroup included younger patients than the other two clusters, and showed the highest ratios of social deprivation and severe mental disease; 48% of its CCPs belonged to the high-risk stratum of the GMA. A third cluster included patients who belonged to the high-risk stratum of the GMA. Their age was similar to that of the patients in the first cluster, but they showed the highest values in the following areas: (i) risk of admission; (ii) proportion of advanced chronic disease and limited-life prognosis; (iii) functional loss and (iv) geriatric syndromes, along with special uncertainty in decision-making and clinical management.Conclusions: Characterization of CCPs shows clearly distinct profiles of needs, which provides an improved epidemiological picture by identifying clusters of patients who are likely to benefit from targeted interventions.

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