Comparison of the information provided by electronic health records data and a population health survey to estimate prevalence of selected health conditions and multimorbidity

This is a freely-available open access publication. Please cite the published version which is available via the DOI link in this record.Background Health surveys (HS) are a well-established methodology for measuring the health status of a population. The relative merit of using information based on HS versus electronic health records (EHR) to measure multimorbidity has not been established. Our study had two objectives: 1) to measure and compare the prevalence and distribution of multimorbidity in HS and EHR data, and 2) to test specific hypotheses about potential differences between HS and EHR reporting of diseases with a symptoms-based diagnosis and those requiring diagnostic testing. Methods Cross-sectional study using data from a periodic HS conducted by the Catalan government and from EHR covering 80% of the Catalan population aged 15 years and older. We determined the prevalence of 27 selected health conditions in both data sources, calculated the prevalence and distribution of multimorbidity (defined as the presence of ≥2 of the selected conditions), and determined multimorbidity patterns. We tested two hypotheses: a) health conditions requiring diagnostic tests for their diagnosis and management would be more prevalent in the EHR; and b) symptoms-based health problems would be more prevalent in the HS data. Results We analysed 15,926 HS interviews and 1,597,258 EHRs. The profile of the EHR sample was 52% women, average age 47 years (standard deviation: 18.8), and 68% having at least one of the selected health conditions, the 3 most prevalent being hypertension (20%), depression or anxiety (16%) and mental disorders (15%). Multimorbidity was higher in HS than in EHR data (60% vs. 43%, respectively, for ages 15-75+, P <0.001, and 91% vs. 83% in participants aged ≥65 years, P <0.001). The most prevalent multimorbidity cluster was cardiovascular. Circulation disorders (other than varicose veins), chronic allergies, neck pain, haemorrhoids, migraine or frequent headaches and chronic constipation were more prevalent in the HS. Most symptomatic conditions (71%) had a higher prevalence in the HS, while less than a third of conditions requiring diagnostic tests were more prevalent in EHR. Conclusions Prevalence of multimorbidity varies depending on age and the source of information. The prevalence of self-reported multimorbidity was significantly higher in HS data among younger patients; prevalence was similar in both data sources for elderly patients. Self-report appears to be more sensitive to identifying symptoms-based conditions. A comprehensive approach to the study of multimorbidity should take into account the patient perspective.Ministry of Science and Innovation through the Instituto Carlos IIIISCiii-RETICSInstitut Universitari d’Investigació en Atenció Primària Jordi Gol (IDIAP Jordi Gol

Socio-economic status and the risk of developing hand, hip or knee osteoarthritis: a region-wide ecological study

SummaryObjectiveTo determine the association between socio-economic status (SES) and risk of hand, hip or knee osteoarthritis (OA) at a population level.DesignRetrospective ecological study using the System for the Development of Research in Primary Care (SIDIAP) database (primary care anonymized records for >5 million people in Catalonia (Spain)). Urban residents >15 years old (2009–2012) were eligible. Outcomes: Validated area-based SES deprivation index MEDEA (proportion of unemployed, temporary workers, manual workers, low educational attainment and low educational attainment among youngsters) was estimated for each area based on census data as well as incident diagnoses (ICD-10 codes) of hand, hip or knee OA (2009–2012). Zero-inflated Poisson models were fitted to study the association between MEDEA quintiles and the outcomes.ResultsCompared to the least deprived, the most deprived areas were younger (43.29 (17.59) vs 46.83 (18.49), years (Mean SD), had fewer women (49.1% vs 54.8%), a higher percentage of obese (16.2% vs 8.4%), smokers (16.9% vs 11.9%) and high-risk alcohol consumption subjects (1.5% vs 1.3%). Compared to the least deprived, the most deprived areas had an excess risk of OA: age-sex-adjusted Incidence Rate Ratio (IRR) 1.26 (1.11–1.42) for hand, 1.23 (1.17–1.29) hip, and 1.51 (1.45–1.57) knee. Adjustment for obesity attenuated this association: 1.06 (0.93–1.20), 1.04 (0.99–1.09), and 1.23 (1.19–1.28) respectively.ConclusionsDeprived areas have higher rates OA (hand, hip, knee). Their increased prevalence of obesity accounts for a 50% of the excess risk of knee OA observed. Public health interventions to reduce the prevalence of obesity in this population could reduce health inequalities

Nanoinformatics: developing new computing applications for nanomedicine

Nanoinformatics has recently emerged to address the need of computing applications at the nano level. In this regard, the authors have participated in various initiatives to identify its concepts, foundations and challenges. While nanomaterials open up the possibility for developing new devices in many industrial and scientific areas, they also offer breakthrough perspectives for the prevention, diagnosis and treatment of diseases. In this paper, we analyze the different aspects of nanoinformatics and suggest five research topics to help catalyze new research and development in the area, particularly focused on nanomedicine. We also encompass the use of informatics to further the biological and clinical applications of basic research in nanoscience and nanotechnology, and the related concept of an extended ?nanotype? to coalesce information related to nanoparticles. We suggest how nanoinformatics could accelerate developments in nanomedicine, similarly to what happened with the Human Genome and other -omics projects, on issues like exchanging modeling and simulation methods and tools, linking toxicity information to clinical and personal databases or developing new approaches for scientific ontologies, among many others

Socio-economic status and the risk of developing hand, hip or knee osteoarthritis: a region-wide ecological study

OBJECTIVE: To determine the association between socio-economic status (SES) and risk of hand, hip or knee osteoarthritis at a population level.DESIGN: Retrospective ecological study using the SIDIAP database (primary care anonymized records for &gt; 5 million people in Catalonia (Spain)). Urban residents &gt; 15 years old (2009-2012) were eligible.OUTCOMES: Validated area-based SES deprivation index MEDEA (proportion of unemployed, temporary workers, manual workers, low educational attainment and low educational attainment among youngsters) was estimated for each area based on census data as well as incident diagnoses (ICD-10 codes) of hand, hip or knee osteoarthritis (2009-2012). Zero-inflated Poisson models were fitted to study the association between MEDEA quintiles and the outcomes.RESULTS: Compared to the least deprived, the most deprived areas were younger (43.29 (17.59) versus 46.83 (18.49), years (Mean SD), had fewer women (49.1% versus 54.8 %), a higher percentage of obese (16.2 % versus 8.4 %), smokers (16.9 % versus 11.9%) and high-risk alcohol consumption subjects (1.5% versus 1.3 %). Compared to the least deprived, the most deprived areas had an excess risk of osteoarthritis: age-sex-adjusted IRR 1.26 (1.11-1.42) for hand, 1.23 (1.17-1.29) hip, and 1.51 (1.45-1.57) knee. Adjustment for obesity attenuated this association: 1.06 (0.93 -1.20), 1.04 (0.99-1.09), and 1.23 (1.19-1.28) respectively.CONCLUSIONS: Deprived areas have higher rates osteoarthritis (hand, hip, knee). Their increased prevalence of obesity accounts for a 50% of the excess risk of knee osteoarthritis observed. Public health interventions to reduce the prevalence of obesity in this population could reduce health inequalities<br/