Special Issue "Secondary Health Data for Monitoring Chronic Health Conditions and Assessing Healthcare Performances"
A special issue of International Journal of Environmental Research and Public Health (ISSN 1660-4601). This special issue belongs to the section "Health Care Sciences & Services".
Deadline for manuscript submissions: 31 March 2023 | Viewed by 652
Interests: biostatistics; epidemiological studies; secondary health data; chronic diseases; disease determinants; healthcare assessment
Interests: biostatistics; nucleic acid quantification; epidemiology; sports health; nutrition
Interests: biostatistics; epidemiology; secondary health data; chronic diseases; disease determinants; health disparities; frailty
Chronic diseases are a threat to people’s health and to the sustainability of health organisations. Despite the considerable amount of research conducted during the past few decades to describe the epidemiology and the impact on the health of chronic diseases, because of the population aging, the disease burden and multimorbidity have increased, leading to higher patient frailty. Therefore, new evidence is needed to assess the impact of chronicity in the population, its evolution over time, the impact of new technologies in disease management and to design appropriate adaptation to health policies. In this context, the availability of health data from secondary sources, such as administrative or healthcare utilization databases, medical record databases, population-based disease registries, hospital-based disease registries, health surveys, represents a useful tool to estimate disease burden and monitoring and assessing healthcare interventions. The large population covered, the continuity and timeliness of data availability, low cost, and applicability for studying real-world practice are characteristics that have contributed to the increased use of these secondary data sources in epidemiological studies. On the other hand, challenges in using these data and strategies to improve their usefulness concern the quality of the data and the application of rigorous and standardized methodology for planning and conducting observational studies, which are rapidly evolving.
This Special Issue of IJERPH is addressed to studies using secondary health data for monitoring chronic health conditions, analysing their determinants, and evaluating healthcare interventions in chronic patients.
Prof. Dr. Edlira Skrami
Dr. Davide Sisti
Prof. Dr. Rosaria Gesuita
Manuscript Submission Information
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- secondary health databases
- chronic diseases
- real-world evidence
- real-world data
- disease burden
- healthcare assessment
- healthcare monitoring
- value-based healthcare
The below list represents only planned manuscripts. Some of these manuscripts have not been received by the Editorial Office yet. Papers submitted to MDPI journals are subject to peer-review.
Title: Integrating administrative health care sources with clinical and instrumental data: the experience of the Observatory of Cardiovascular Diseases.
Authors: Giulia Barbati 1, Arjuna Scagnetto 2, Caterina Gregorio 1, Giovanni Baj 3, Ilaria Gandin 1, Giulia Russo 2, Giorgio Faganello 2, Chiara Cappelletto 2, Annamaria Iorio 4, Andrea Di Lenarda 2
Affiliation: 1 Biostatistics Unit, Department of Medical Sciences, University of Trieste, Trieste, Italy 2 Cardiovascular Center, Azienda Sanitaria Universitaria Giuliano Isontina (ASUGI), Trieste, Italy 3 Department of Mathematics and Geoscience, University of Trieste, Trieste, Italy 4 Cardiology Unit, Papa Giovanni XXIII Hospital Bergamo, Italy
Abstract: Over the last decades an increasing interest in integrating administrative healthcare data with clinical informations from Electronic Health Records (EHR) has been observed in the epidemiological community. The advantages of this integration reside mainly in the spatio-temporal coverage at a community-based level and the data availability at a relatively low cost, when obstacles related to data access are overcome. The main challenges are related to the identification of the target population and the risk of exposure/disease misclassification. Variables of interest are in fact derived from complex algorithms based on the linkage of multiple sources, often in a longitudinal design. In the present work, the experience of the Cardiovascular Observatory located in the Friuli-Venezia-Giulia Region (north-east of Italy) is presented, together with a review of the principles and methods that have guided us. We also discuss our current challenge, i.e. integrating more heterogenous sources, like ECG (electrocardiogram) signals to the administrative-EHR tabular data with the aim to implement artificial intelligence (AI) tools to further enrich the diagnostic and prognostic epidemiological models.