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Background and Aims: Data from clinical trials suggest that biological drugs may improve the outcomes in Crohn&rsquo, s disease (CD) by reducing the need for surgery or hospitalization. The aim of this study is to evaluate the time-trends of the use of biological drugs and other treatments for CD, and its relationship with outcomes in Catalonia. Materials and Methods: All patients with CD included in the Catalan Health Surveillance System (containing data on a population of more than 7.5 million) from 2011 to 2017 were identified. The exposures to different treatments for inflammatory bowel disease were retrieved from electronic invoicing records. Results: Between 2011 and 2017, the use of salicylates, corticosteroids and immunosuppressive treatment fell from 28.8% to 17.1%, 15.8% to 13.7%, and 32.9% to 29.6%, respectively (p &lt, 0.001). Biological treatment use rose from 15.0% to 18.7% (p &lt, 0.001). Ostomy rates per 1000 patients/year fell from 13.2 in 2011 to 9.8 in 2017 (p = 0.003), and surgical resection rates from 24.1 to 18.0 (p &lt, 0.001). The rate of CD-related hospitalizations per 1000 patients/year also fell, from 92.7 to 72.2 (p &lt, 0.001). Conclusions: Biological drug use rose from 15.0% to 18.7% between 2011 and 2017. During this period, we observed an improvement in the outcomes of CD patients.

Background Multimorbidity is highly relevant for both service commissioning and clinical decision-making. Optimization of variables assessing multimorbidity in order to enhance chronic care management is an unmet need. To this end, we have explored the contribution of multimorbidity to predict use of healthcare resources at community level by comparing the predictive power of four different multimorbidity measures. Methods A population health study including all citizens ≥18 years (n = 6,102,595) living in Catalonia (ES) on 31 December 2014 was done using registry data. Primary care service utilization during 2015 was evaluated through four outcome variables: A) Frequent attendants, B) Home care users, C) Social worker users, and, D) Polypharmacy. Prediction of the four outcome variables (A to D) was carried out with and without multimorbidity assessment. We compared the contributions to model fitting of the following multimorbidity measures: i) Charlson index; ii) Number of chronic diseases; iii) Clinical Risk Groups (CRG); and iv) Adjusted Morbidity Groups (GMA). Results The discrimination of the models (AUC) increased by including multimorbidity as covariate into the models, namely: A) Frequent attendants (0.771 vs 0.853), B) Home care users (0.862 vs 0.890), C) Social worker users (0.809 vs 0.872), and, D) Polypharmacy (0.835 vs 0.912). GMA showed the highest predictive power for all outcomes except for polypharmacy where it was slightly below than CRG. Conclusions We confirmed that multimorbidity assessment enhanced prediction of use of healthcare resources at community level. The Catalan population-based risk assessment tool based on GMA presented the best combination of predictive power and applicability.

Background Comprehensive assessment of integrated care deployment constitutes a major challenge to ensure quality, sustainability and transferability of both healthcare policies and services in the transition toward a coordinated service delivery scenario. To this end, the manuscript articulates four different protocols aiming at assessing large-scale implementation of integrated care, which are being developed within the umbrella of the regional project Nextcare (2016–2019), undertaken to foster innovation in technologically-supported services for chronic multimorbid patients in Catalonia (ES) (7.5 M inhabitants). Whereas one of the assessment protocols is designed to evaluate population-based deployment of care coordination at regional level during the period 2011–2017, the other three are service-based protocols addressing: i) Home hospitalization; ii) Prehabilitation for major surgery; and, iii) Community-based interventions for frail elderly chronic patients. All three services have demonstrated efficacy and potential for health value generation. They reflect different implementation maturity levels. While full coverage of the entire urban health district of Barcelona-Esquerra (520 k inhabitants) is the main aim of home hospitalization, demonstration of sustainability at Hospital Clinic of Barcelona constitutes the core goal of the prehabilitation service. Likewise, full coverage of integrated care services addressed to frail chronic patients is aimed at the city of Badalona (216 k inhabitants). Methods The population-based analysis, as well as the three service-based protocols, follow observational and experimental study designs using a non-randomized intervention group (integrated care) compared with a control group (usual care) with a propensity score matching method. Evaluation of cost-effectiveness of the interventions using a Quadruple aim approach is a central outcome in all protocols. Moreover, multi-criteria decision analysis is explored as an innovative method for health delivery assessment. The following additional dimensions will also be addressed: i) Determinants of sustainability and scalability of the services; ii) Assessment of the technological support; iii) Enhanced health risk assessment; and, iv) Factors modulating service transferability. Discussion The current study offers a unique opportunity to undertake a comprehensive assessment of integrated care fostering deployment of services at regional level. The study outcomes will contribute refining service workflows, improving health risk assessment and generating recommendations for service selection. Trials registration NCT03130283 (date released 04/06/2018), NCT03768050 (date released 12/05/2018), NCT03767387 (date released 12/05/2018). Electronic supplementary material The online version of this article (10.1186/s12913-019-4174-2) contains supplementary material, which is available to authorized users.

BackgroundClinical management of patients with chronic obstructive pulmonary disease (COPD) shows potential for improvement provided that patients’ heterogeneities are better understood. The study addresses the impact of comorbidities and its role in health risk assessment.ObjectiveTo explore the potential of health registry information to enhance clinical risk assessment and stratification.DesignFixed cohort study including all registered patients with COPD in Catalonia (Spain) (7.5 million citizens) at 31 December 2014 with 1-year (2015) follow-up.MethodsA total of 264 830 patients with COPD diagnosis, based on the International Classification of Diseases (Ninth Revision) coding, were assessed. Performance of multiple logistic regression models for the six main dependent variables of the study: mortality, hospitalisations (patients with one or more admissions; all cases and COPD-related), multiple hospitalisations (patients with at least two admissions; all causes and COPD-related) and users with high healthcare costs. Neither clinical nor forced spirometry data were available.ResultsMultimorbidity, assessed with the adjusted morbidity grouper, was the covariate with the highest impact in the predictive models, which in turn showed high performance measured by the C-statistics: (1) mortality (0.83), (2 and 3) hospitalisations (all causes: 0.77; COPD-related: 0.81), (4 and 5) multiple hospitalisations (all causes: 0.80; COPD-related: 0.87) and (6) users with high healthcare costs (0.76). Fifteen per cent of individuals with highest healthcare costs to year ratio represented 59% of the overall costs of patients with COPD.ConclusionsThe results stress the impact of assessing multimorbidity with the adjusted morbidity grouper on considered health indicators, which has implications for enhanced COPD staging and clinical management.Trial registration numberNCT02956395.

Background: Health risk assessment and stratification have proven highly relevant for large-scale implementation of integrated care by facilitating services design and case identification. Aim: The principal objective was to analyse five health-risk assessment strategies used in the five regions participating in the Advancing Care Coordination and TeleHealth Deployment (ACT) program (www.act-programme.eu): Scotland (UK), Basque Country (ES), Catalonia (ES), Lombardy (I) and Groningen (NL). A second aim was to explore the potential of population-based health risk predictive tools to contribute to risk prediction in the clinical setting. Method: We characterized and compared risk assessment strategies among ACT regions by analysing operational risk predictive modelling tools for population-based stratification, as well as available health indicators. The risk assessment tool deployed in Catalonia (GMA, Adjusted Morbidity Groups) was used as an example to explore how population-based analysis can contribute to clinical risk prediction. Results: The study indicated a high degree of conceptual agreement among the five ACT regions on the relevant role of population-based health risk assessment for regional deployment of integrated care. The entire ACT consortium shared its usefulness for service commission, case finding and screening. There was also consensus on the use of a population health approach as the optimal strategy for population-based risk assessment. However, the health risk predictive modelling tools in place displayed marked heterogeneities that precluded comparability of the risk pyramid distributions across regions. We identified a clear need for evolving toward risk predictive modelling tools allowing proper quantification of the estimations. Likewise, different well-identified problems mostly associated to data reporting precluded appropriate comparisons of the recommended health indicators. The current study identified transferability across regions and potential for evolving, that is flexibility, as two key requirements for any population-based health risk assessment tool. Factors such as: i) license binding constraints, ii) insufficient public availability; iii) lack of availability for inspection; and/or, iv) rigidity of some computational algorithms (i.e. due to inclusion of expert-based criteria in some morbidity groupers) are currently limiting transferability. These factors might also preclude adaptation of the current risk prediction tools toward evolving requirements such as: i) integration between healthcare and social services; and, ii) implementation of synergies between population-based and clinically oriented risk predictive modelling, as described in the study. We acknowledge some intrinsic limitations of population-based predictive modelling in terms of strength of estimations. However, their potential for allocation of individuals into the risk stratification pyramid facilitates both design and implementation of preventive strategies that have shown high potential to generate healthcare value. Moreover, the study reports on the conceptual steps required for development of innovative strategies for clinical risk predictive modelling with potential to enhance its supporting role for decision making in the clinical scenario. Conclusions : We acknowledge that further efforts should be devoted to improve both comparability and flexibility of current population-based health risk predictive modelling approaches. The novel strategy for enhanced clinical risk assessment requires prospective evaluation.