Literature DB >> 21148154

DANBIO--powerful research database and electronic patient record.

Merete Lund Hetland1.   

Abstract

The nationwide DANBIO registry has been designed to capture operational clinical data as part of routine clinical care. At the same time, it provides a powerful research database. This article reviews the DANBIO registry with focus on problems and solutions of design, funding and linkage, provides an overview of the research outcome and presents the cohorts of RA patients. The registry, which is approved as a national quality registry, includes patients with RA, PsA and AS, who are followed longitudinally. Data are captured electronically from the source (patients and health personnel). The IT platform is based on open-source software. Via a unique personal identification code, linkage with various national registers is possible for research purposes. Since the year 2000, more than 10,000 patients have been included. The main focus of research has been on treatment efficacy and drug survival. Compared with RA patients, who were on conventional treatment with DMARDs, the patients who started biological treatment were younger, had longer disease duration, higher disease activity, tried more DMARDs and received more prednisolone. Also, more patients on biological therapy were seropositive and had erosive disease. However, the current levels of disease activities and the fraction of patients who had gone into remission in the two groups of patients were very similar. This indicates that clinicians have a common treatment goal for RA patients regardless of treatment. In conclusion, DANBIO serves as an electronic patient 'chronicle' in routine care, and at the same time provides a powerful research database.

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Year:  2011        PMID: 21148154     DOI: 10.1093/rheumatology/keq309

Source DB:  PubMed          Journal:  Rheumatology (Oxford)        ISSN: 1462-0324            Impact factor:   7.580


  42 in total

Review 1.  Review and evaluation of electronic health records-driven phenotype algorithm authoring tools for clinical and translational research.

Authors:  Jie Xu; Luke V Rasmussen; Pamela L Shaw; Guoqian Jiang; Richard C Kiefer; Huan Mo; Jennifer A Pacheco; Peter Speltz; Qian Zhu; Joshua C Denny; Jyotishman Pathak; William K Thompson; Enid Montague
Journal:  J Am Med Inform Assoc       Date:  2015-07-29       Impact factor: 4.497

Review 2.  Big data and data processing in rheumatology: bioethical perspectives.

Authors:  Amaranta Manrique de Lara; Ingris Peláez-Ballestas
Journal:  Clin Rheumatol       Date:  2020-02-15       Impact factor: 2.980

3.  Cardiovascular risk profiles in a hospital-based population of patients with psoriatic arthritis and ankylosing spondylitis: a cross-sectional study.

Authors:  Christoffer B Nissen; Kim Hørslev-Petersen; Jette Primdahl
Journal:  Rheumatol Int       Date:  2016-11-26       Impact factor: 2.631

4.  Test-retest of computerized health status questionnaires frequently used in the monitoring of knee osteoarthritis: a randomized crossover trial.

Authors:  Henrik Gudbergsen; Else M Bartels; Peter Krusager; Eva E Wæhrens; Robin Christensen; Bente Danneskiold-Samsøe; Henning Bliddal
Journal:  BMC Musculoskelet Disord       Date:  2011-08-18       Impact factor: 2.362

5.  Sex differences in response to anti-tumor necrosis factor therapy in early and established rheumatoid arthritis -- results from the DANBIO registry.

Authors:  Damini Jawaheer; Jørn Olsen; Merete Lund Hetland
Journal:  J Rheumatol       Date:  2011-11-15       Impact factor: 4.666

6.  Interplay between patient global assessment, pain, and fatigue and influence of other clinical disease activity measures in patients with active rheumatoid arthritis.

Authors:  Emilie Lund Egsmose; Ole Rintek Madsen
Journal:  Clin Rheumatol       Date:  2015-05-19       Impact factor: 2.980

7.  Confirmation of an IRAK3 polymorphism as a genetic marker predicting response to anti-TNF treatment in rheumatoid arthritis.

Authors:  J Sode; U Vogel; S Bank; P S Andersen; M L Hetland; H Locht; N H H Heegaard; V Andersen
Journal:  Pharmacogenomics J       Date:  2016-10-04       Impact factor: 3.550

8.  Fatigue, pain and patient global assessment responses to biological treatment are unpredictable, and poorly inter-connected in individual rheumatoid arthritis patients followed in the daily clinic.

Authors:  Ole Rintek Madsen; Eva Marie Egsmose
Journal:  Rheumatol Int       Date:  2016-07-23       Impact factor: 2.631

9.  Stability of clinical outcome measures in rheumatoid arthritis patients with stable disease defined on the basis of the EULAR response criteria.

Authors:  Ole Rintek Madsen
Journal:  Clin Rheumatol       Date:  2016-06-09       Impact factor: 2.980

10.  Implementing an automated monitoring process in a digital, longitudinal observational cohort study.

Authors:  Lisa Lindner; Anja Weiß; Andreas Reich; Siegfried Kindler; Frank Behrens; Jürgen Braun; Joachim Listing; Georg Schett; Joachim Sieper; Anja Strangfeld; Anne C Regierer
Journal:  Arthritis Res Ther       Date:  2021-07-07       Impact factor: 5.156

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